A pilot flying his plane over the South Pacific sees an uncharted island in the distance and circles downward to take a closer look. As the plane descends, the pilot spots large rocks on the island’s shore arranged to spell out SOS. Beyond the reach of waves, he notices a grass hut. Without hesitation, the pilot radios for help.
Is this pilot behaving rationally? No one would question the point. He recognizes the improbability of wind and waves acting on the rocks along the shore to spell SOS.1 Experience has taught the pilot that intelligible messages must come from intelligent sources. SOS, though not a word in the English language, represents the code for the universal distress message. The island inhabitant spelled out not just a word, such as “help,” but a special code, SOS, on the beach knowing that anyone seeing it from the air would recognize its meaning.
The grass hut also convinces the pilot to radio for help. It provides further evidence that the rocks’ arrangement on the beach is not the effect of chance, but rather the work of someone stranded on the island. Encoded information coupled with additional evidence for intelligent activity provides support for design that goes beyond the mere presence of information. It requires an intelligent agent to choose and employ the code. And, encoded information carries an implied sense of purpose.
Over the last 40 years, scientists have found the same type of evidence inside the cell that prompted the pilot’s radio call for help. They have discovered that the cell’s biochemical machinery is an information-based system. Moreover, the chemical information inside the cell exists as encoded information. The genetic code (the rules used to encode the cell’s information) defines the cell’s biochemical information system.
By itself, the cell’s encoded information offers powerful evidence for an Intelligent Designer. And, like the islander’s grass hut, recent discoveries provide additional proof validating the premise. Molecular biologists studying the genetic code’s origin have unwittingly stumbled across profound evidence for Intelligent Design—a type of fine-tuning in the rules that form the genetic code. These rules impart to the genetic code the surprising capacity to minimize errors.
Error-minimization properties in the genetic code allow the cell’s biochemical information systems to make mistakes and still communicate critical information with high fidelity. It’s as if the stranded island inhabitant could arrange the rocks as SSO or OSS and still communicate the need for help.
Much as the islander’s message began with the rocks, the description of cellular information begins with proteins. Proteins, the “workhorse” molecules of life, take part in essentially every cellular and extracellular structure and activity. They help form structures inside the cell and in the cell’s surrounding matrix. Among other roles, proteins catalyze chemical reactions, harvest chemical energy, serve in the cell’s defense systems, and store and transport molecules.2
Molecules called polypeptides make up proteins. One or more of the same and/or different polypeptides interact to form proteins. Polypeptides are chain-like molecules folded into precise three-dimensional structures. The polypeptide’s three-dimensional architecture determines the way one polypeptide interacts with other polypeptides to form a protein. The structure of the polypeptide consequently dictates its function.3
Polypeptides form when the cellular machinery links together (in a head-to-tail fashion) smaller subunit molecules called amino acids.4 The cell employs 20 different amino acids to make polypeptides. The amino acids that make up the cell’s polypeptide chains possess a variety of chemical and physical properties.5 In principle, the 20 amino acids can link up in any of the possible amino acid combinations and sequences to form a polypeptide.
Each amino acid sequence imparts the polypeptide with a unique chemical and physical profile along its chain. The chemical and physical profile determines how the polypeptide chain folds, and, therefore, how it interacts with other polypeptide chains to form a functional protein. Because structure determines the function of a polypeptide, the amino acid sequence ultimately defines the type of work the polypeptide performs.
A polypeptide’s amino acid sequence contains information. Just as letters form words, amino acids strung together form the “words” of the cell, polypeptides.6 In language, some letter combinations produce meaningful words and others produce gibberish. Amino acid sequences do the same. Some produce functional polypeptides, whereas others produce gibberish polypeptides that serve no role inside the cell.7
Treating amino acid sequences as information has become a fruitful approach for researchers seeking to understand the origin of proteins.8 It has also helped them characterize the functional utility of different amino acid sequences.
DNA, like polypeptides, contains information. In fact, DNA’s chief function is information storage.
Like proteins, DNA consists of chain-like molecules known as polynucleotides.9 Two polynucleotide chains align in an antiparallel fashion to form a DNA molecule. (The two strands are arranged parallel to one another with the starting point of one strand located next to the ending point of the other strand, and vice versa.) The paired polynucleotide chains twist around each other forming the well-known DNA double helix. The cell’s machinery forms polynucleotide chains by linking together four different subunit molecules called nucleotides. The four nucleotides used to build DNA chains are adenosine, guanosine, cytidine, and thymidine, familiarly known as A, G, C, and T, respectively.
DNA stores the information necessary to make all the polypeptides used by the cell. The sequence of nucleotides in the DNA strands specifies the sequence of amino acids in polypeptide chains. Scientists refer to the amino-acid-coding nucleotide sequence (for constructing polypeptides) along the DNA strand as a gene.10 Through the use of genes, DNA stores the information functionally expressed in the amino acid sequences of polypeptide chains. The DNA strands’ nucleotides function as alphabet letters and the genes as words.
Central Dogma of Molecular Biology
No discussion of biochemical information systems would be complete without considering information “flow” inside the cell, known as the “central dogma of molecular biology.”11 This concept describes how information stored in DNA becomes functionally expressed through the amino acid sequence and activity of polypeptide chains.
Found inside the nucleus of complex cells, DNA can be compared to the reference books found in a library. The information stored there cannot be removed but must be copied, or transcribed. DNA does not leave the nucleus to direct the synthesis of polypeptide chains. Rather the cellular machinery copies the gene’s sequence by assembling another polynucleotide, messenger RNA (mRNA).12 This single-strand molecule is similar, but not identical, in composition to DNA. One of the most important differences between DNA and mRNA is the use of uridine (U) in place of thymidine (T) to form the mRNA chain. Scientists refer to the process of copying mRNA from DNA as transcription.
Once assembled, mRNA migrates from the nucleus of the cell into the cytoplasm. At the ribosome, mRNA directs the synthesis of polypeptide chains.13 The information content of the polynucleotide sequence is translated into the polypeptide amino acid sequence–– much like translating Spanish into English.
The analogical language used to describe the flow of information in biochemical systems is no accident. Biochemical systems are information systems.
The Genetic Code
Life’s Encoded Information
One may wonder how the sequence of nucleotides in DNA translates into the sequence of amino acids in a polypeptide. There seems to be a mismatch between the storage and functional expression of information in the cell. A one-to-one relationship cannot exist between the four different nucleotides of DNA and the 20 different amino acids used to assemble polypeptides. The cell overcomes this mismatch by using a code comprised of groupings of three nucleotides to specify the 20 different amino acids.14
The cell uses a set of rules to relate these nucleotide triplet sequences to the 20 amino-comprising polypeptides. Molecular biologists refer to this set of rules as the genetic code. The nucleotide triplets, or “codons” as they are called, represent the fundamental communication units of the genetic code. In the same way that the stranded islander used three letters, SOS, to communicate his plight, the genetic code uses three nucleotide “characters” to signify an amino acid. The genetic code is essentially universal among all living organisms.
Sixty-four codons make up the genetic code. Because the genetic code only needs to encode 20 amino acids, some of the codons are redundant. That is, different codons code for the same amino acid. In fact, up to six different codons specify some amino acids. Others are specified by only one codon.
Interestingly, some codons, called stop codons or nonsense codons, code no amino acids. (For example, the codon UGA is a stop codon.) These codons always occur at the end of the gene, informing the cell where the polypeptide chain ends. Stop codons serve as a form of “punctuation” for the cell’s information system.
Some coding triplets, called start codons, play a dual role in the genetic code. These codons not only encode amino acids, but also “tell” the cell where a polypeptide begins. For example, the codon GUG not only encodes the amino acid valine, it also specifies the starting point of the polypeptide chain. Start codons function as a sort of “capitalization” for the information system of the cell.
The Genetic Code and Intelligent Design
Observed information on the island leads the pilot to reasonably conclude that an intelligent agent designed it with a purpose. The information content of DNA and proteins, the molecules that ultimately define life’s most fundamental structures and processes, leads to the inescapable conclusion that an Intelligent Designer with purpose in mind is responsible for life. This conclusion is as rational as the one made by the pilot when he spotted the message on the beach and radioed for help.
The genetic code, the set of rules that translate the stored information found in DNA into the functional information of proteins, provides further support for an Intelligent Designer. All codes require an intelligent agent to develop the set of rules defining the code.
The set of rules that define the genetic code, universal to all life, reveals still more amazing evidence for design. The genetic code displays a fascinating capacity to resist the errors that naturally occur as the cell uses information or transmits information from one generation to the next. Qualitative inspection of the code only partly exposes its fine-tuning. Recent studies employing methods to quantify error-minimization properties in the genetic code bring this new evidence for Intelligent Design squarely into focus.
Why does the error-minimization capacity of the genetic code provide such a powerful indicator for Intelligent Design? Translating the stored information of DNA into the functional information of proteins is the genetic code’s chief function. The genetic code’s failure to transmit and translate information with high fidelity can be devastating to the cell. Briefly considering how mutations affect cells facilitates understanding.
A mutation refers to any change that takes place in the DNA nucleotide sequence.15 DNA can experience several different types of mutations. Substitution mutations are one common type. In a substitution mutation, one or more of the nucleotides in the DNA strand is replaced by another nucleotide. For example, an A may be replaced by a G, or a C may be replaced by a T. This substitution changes the codon that the nucleotide is part of. The amino acid specified by that codon changes, leading to an altered chemical and physical profile along the polypeptide chain. If the substituted amino acid possesses dramatically different physicochemical properties from the native amino acid, the polypeptide folds improperly. This improper folding impacts the polypeptide, and hence yields a protein with reduced or even lost function. Most mutations harm cellular health because they significantly and negatively impact protein structure and function.
Qualitative Design Evidence
The genetic code’s redundancy appears to be well thought out rather than haphazard. Genetic code rules incorporate a design that allows the cell to avoid the harmful effects of substitution mutations. For example, six codons encode the amino acid leucine (Leu). If at a particular amino acid position in a polypeptide, Leu is encoded by 5′ (pronounced five prime, a marker indicating the beginning of the codon). CUU, substitution mutations in the 3′ position from U to C, A, or G produce three new codons, 5′ CUC, 5′ CUA, and 5′ CUG, all of which code for Leu. The net effect produces no change in the amino acid sequence of the polypeptide. For this scenario, the cell successfully avoids the negative effects of a substitution mutation.
Likewise, a change of C in the 5′ position to a U generates a new codon, 5’UUU, that specifies phenylalanine, an amino acid with similar physical and chemical properties to Leu. A change of C to an A or to a G produces codons that code for isoleucine and valine, respectively. These two amino acids also possess chemical and physical properties similar to leucine. Qualitatively, the genetic code appears constructed to minimize errors that result from substitution mutations.
Quantitative Design Evidence
Recently, scientists from the University of Bath (U.K.) and from Princeton University worked to quantify the error-minimization capacity of the genetic code. Early work indicated that the naturally occurring genetic code withstands the potentially harmful effects of substitution mutations better than all but 0.02 percent (1 out of 5000) of randomly generated genetic codes with codon assignments different from the universal genetic code.16
This initial work overlooked the fact that some types of substitution mutations occur more frequently than others in nature. For example, an A-to-G substitution occurs more frequently than does either an A-to-C or an A-to-T mutation. When researchers incorporated this correction into their analysis, they discovered that the naturally occurring genetic code performed better than one million randomly generated genetic codes. They also found that the genetic code in nature resides near the global optimum for all possible genetic codes with respect to its error-minimization capacity.17 Nature’s universal genetic code is truly one in a million—or better!
The genetic code’s error-minimization properties are actually more dramatic than these results indicate. When researchers calculated the error-minimization capacity of one million randomly generated genetic codes, they discovered that the error-minimization values formed a distribution where the naturally occurring genetic code’s capacity occurred outside the distribution.18 Researchers estimate the existence of 1018 possible genetic codes possessing the same type and degree of redundancy as the universal genetic code. All of these codes fall within the error-minimization distribution. This finding means that of 1018 possible genetic codes, few, if any, have an error-minimization capacity that approaches the code found universally in nature.
Obviously concerned about the implications, some researchers have challenged the optimality of the genetic code.19 The teams from Bath, Princeton, and elsewhere, however, have effectively responded to these challenges.20
A Force Behind the Genetic Code
Based on their research results, the Bath and Princeton scientists concluded that the rules of the genetic code could not be a frozen accident. A genetic code assembled through random biochemical events would not possess near ideal error-minimization properties. These researchers argue that a “force” shaped the genetic code. Instead of looking to a supernatural explanation for the genetic code’s origin, however, they appeal to natural selection. They believe random events operated on by “the forces of natural selection” over and over again produced the genetic code’s error-minimization capacity.21
Can the Genetic Code Evolve?
Other scientific work questions the likelihood that the genetic code evolved. In 1968 Nobel Laureate Francis Crick, in a classic paper, convincingly argued that the genetic code could not have undergone significant evolution.22 The rationale for Crick’s position is easy to understand. Any change in codon assignment leads to changes in amino acids in every polypeptide made by the cell. This wholesale change in polypeptide sequences would result in large numbers of defective proteins. Nearly any conceivable change to the genetic code would be lethal to the cell.
Even if the genetic code could change gradually over time to yield a set of rules that allowed for maximum error-minimization capacity, is there enough time for this process to occur? Biophysicist Hubert Yockey has addressed this question.23 He calculates that natural selection would have to explore 1.40 x 1070 different genetic codes to hit upon the universal genetic code found in nature. Yockey estimates the maximum time available for the code to originate as 6.3 x 1015 seconds. Put simply, natural selection lacks adequate time to find the universal genetic code. It would have to evaluate about 1054 codes per second.
Other researchers suggest that the genetic code’s origin coincides with the origin of life. Operating within the evolutionary paradigm, a team headed by renowned origin-of-life researcher Manfred Eigen estimated the age of the genetic code as 3.8 + 0.6 billion years.24 Current geochemical evidence places life’s first appearance on Earth at 3.86 billion years ago.25
The Supernatural Origin of the Gentic Code
The genetic code—the set of rules used by the cell to translate information stored in DNA into the information used by polypeptides—possesses a virtually unique optimality in its capacity to resist errors caused by mutation. The genetic code in every way defies explanation as a frozen accident produced by random biochemical events, or as the fortuitous outcome of an evolutionary process directed by the blind forces of natural selection. Genetic code evolution would be catastrophic for the cell. Given the rapidity of life’s origin, time is too short for natural selection to come across the well-designed universal genetic code found in nature. The genetic code seemingly originates at the time life first appears on Earth. All this evidence dictates the conclusion that an Intelligent Designer is responsible for the genetic code.
This conclusion becomes even more compelling when one considers that encoded information demands an intelligent agent not only to generate the information, but also to design and apply the set of rules that constitute the code. The remarkable fine-tuning of the genetic code provides cohesive corroborative evidence for the biblical Intelligent Designer. Like the SOS rock formation and the grass hut on the beach, the genetic code offers every indication that a Creator deliberately and purposefully shaped the message.
The scientists from the University of Bath and Princeton University, fully aware of Francis Crick’s work, still rely on evolution to explain the genetic code’s optimal design because of the existence of nonuniversal genetic codes. While the genetic code in nature is generally regarded as universal, some nonuniversal genetic codes exist—genetic codes that employ slightly modified codon assignments. Presumably these nonuniversal genetic codes evolved from the universal genetic code. Therefore, researchers argue that genetic code evolution is possible. For the most part, however, the codon assignments of the nonuniversal genetic codes are identical to that of the universal genetic code with only one or two codon assignments being different. It is better to think of the nonuniversal genetic codes as deviants of the universal genetic code.
Does the existence of nonuniversal genetic codes imply that wholesale genetic code evolution is possible? The answer is no. Careful study reveals that codon changes in the nonuniversal genetic codes always occur in relatively small genomes, such as mitochondrial genomes, and involve either: (1) codons that occur at low frequencies in that particular genome; or (2) stop codons. Changes in assignment for these codons could occur without producing a lethal scenario, since only a small number of polypeptides in the cell or organelle would experience an altered amino acid sequence. Thus, it appears that limited evolution of the genetic code can take place, but only in special circumstances.1
- Peter Kreeft, Fundamentals of the Faith: Essays in Christian Apologetics (San Francisco: Ignatius Press, 1988), 25-26.
- Robert C. Bohinksi, Modern Concepts in Biochemistry, 4th ed. (Boston: Allyn and Bacon, 1983), 86-87.
- Harvey Lodish et al., Molecular Cell Biology, 4th ed. (New York: W. H. Freeman, 2000), 54-60.
- Lodish et al., 51-54.
- Lodish et al., 52.
- Michael Denton, Evolution: A Theory in Crisis (Bethesda, MD: Adler & Adler, 1986), 308-25; Walter L. Bradley and Charles B. Thaxton, “Information and the Origin of Life,” in The Creation Hypothesis: Scientific Evidence for an Intelligent Designer, ed. J. P. Moreland (Downers Grove, IL: InterVaristy Press, 1994), 188-90.
- Lodish et al., 257.
- Hubert P. Yockey, Information Theory and Molecular Biology (Cambridge: Cambridge University Press, 1992); Charles B. Thaxton, Walter L. Bradley, and Roger L. Olsen, The Mystery of Life’s Origin: Reassessing Current Theories (Dallas: Lewis and Stanley, 1984), 127-43; Bernd-Olaf Küppers, Information and the Origin of Life, (Cambridge, MA: The MIT Press, 1990).
- Lodish et al., 101-05.
- The gene structure is far more complex than portrayed here. Any biochemistry or molecular biology textbook can be consulted for a more thorough discussion of gene structure.
- David Freifelder, Molecular Biology, 2d ed. (Boston, MA: Jones and Bartlett Publishers, 1987), 208.
- Lodish et al., 111-116.
- Lodish et al., 125-34.
- Lodish et al., 117-20.
- Lubert Stryer, Biochemistry, 3d ed. (New York: W. H. Freeman, 1988), 675-76.
- David Haig and Laurence D. Hurst, “A Quantitative Measure of Error Minimization in the Genetic Code,” Journal of Molecular Evolution 33 (1991): 412-17.
- Gretchen Vogel, “Tracking the History of the Genetic Code,” Science 281 (1998), 329-31; Stephen J. Freeland and Laurence D. Hurst, “The Genetic Code Is One in a Million,” Journal of Molecular Evolution 47 (1998): 238-48; Stephen J. Freeland et al., “Early Fixation of an Optimal Genetic Code,” Molecular Biology and Evolution 17 (2000): 511-18.
- Freeland and Hurst, 238-48.
- Massimo D. Giulio, “The Origin of the Genetic Code,” Trends in Biochemical Sciences 25 (2000): 44.
- Stephen J. Freeland, Robin D. Knight and Laura F. Landweber, “Measuring Adaptation within the Genetic Code,” Trends in Biochemical Sciences 25 (2000): 44; Stephen J. Freeland and Laurence D. Hurst, “Load Minimization of the Genetic Code: History Does Not Explain the Pattern,” Proceedings of the Royal Society of London B 265 (1998): 2111-19; Terres A. Ronneberg, Laura F. Landweber and Stephen J. Freeland, “Testing a Biosynthetic Theory of the Genetic Code: Fact or Artifact?” Proceedings of the National Academy of Sciences, USA 97 (2000): 13690-95; Ramin Amirnovin, “An Analysis of the Metabolic Theory of the Origin of the Genetic Code,” Journal of Molecular Evolution 44 (1997): 473-76.
- Robin D. Knight, Stephen J. Freeland and Laura F. Landweber, “Selection, History and Chemistry: The Three Faces of the Genetic Code,” Trends in Biochemical Sciences 24 (1999): 241-47.
- F. H. C. Crick, “The Origin of the Genetic Code,” Journal of Molecular Biology 38 (1968): 367-79.
- Yockey, 180-83.
- Manfred Eigen et al., “How Old Is the Genetic Code? Statistical Geometry of tRNA Provides an Answer,” Science 244 (1989), 673-79.
- Fazale Rana, “Origin-of-Life Predictions Face Off: Evolution vs. Biblical Creation,” Facts for Faith 6 (Q2 2001), 41-47.
- Syozo Osawa et al., “Evolution of the Mitochondrial Genetic Code I. Origin of AGR Serine and Stop Codons in Metazoan Mitochondria,” Journal of Molecular Evolution 29 (1989): 202-7; Dennis W. Schultz and Michael Yarus, “On the Malleability in the Genetic Code,” Journal of Molecular Evolution 42 (1996): 597-601; Eors Szathmary, “Codon Swapping as a Possible Evolutionary Mechanism,” Journal of Molecular Evolution 32 (1991): 178-82.