Re: Random origin of biological information

Date: Fri Sep 22 2000 - 11:49:51 EDT

  • Next message: Moorad Alexanian: "Re: atheism vs theism"

    In a message dated 9/22/2000 4:50:01 AM Pacific Daylight Time, writes:

    << But let's look more closely at what really happens in evolution! Hubert
    Yockey ("A calculation of the probability of spontaneous biogenesis by
    information theory", J.theoret.Biol. 67 (1977), 377) compared the then
    known sequences of the small enzyme cytochrome c from different
    He found that 27 of the 101 amino acid positions were completely
    2 different amino acids occurred at 14 positions, 3 at 21, etc., more
    10 nowhere. Optimistically assuming that the 101 positions are mutually
    independent and that chemically similar amino acids can replace each
    at the variable positions without harming the enzymatic activity, he
    calculated that 4 x 10^61 different sequences of 101 amino acids might
    cytochrome c activity. But this implies that the probability of
    emergence of any one of them is only 2 x 10^(-65), which is way too low
    be considered reasonable (it is unlikely that these numbers would change
    appreciably by including all sequences known today). A similar situation
    applies to other enzymes, such as ribonucleases.

    Thus, a modern enzyme activity is extremely unlikely to be found by a
    random-walk mutational process. But "primitive" enzymes, near the origin
    life, may be expected to have much less activity and to be much less
    sensitive to variation. Unfortunately, before someone synthesizes a set
    "primitive" cytochromes c, we have no way of knowing the effects of

    Is this what "really happens in evolution"? Laurie Godfrey in "Scientists
    confront creationism" pp. 89 addresses Yockey and shows the flaws in his

    Or see

    "Yockey also generates another misquoted number. Assuming the maximimum
    number of suitable planets and amino-acids, the known age of the
    universe, and a recombination rate of twice per day (on average), he tells us
    that 1.61 x 10^60 different 100-amino-acid chains will be produced.
    This in no way refers to the odds against life, since Yockey does not try to
    figure how many of those combinations would be viable (certainly it
    would not be only one), and all the same problems apply here as before.
    Nevertheless, this number is cited as if it were a statistic by Bradley and
    Thaxton in The Creation Hypothesis (discussed below)--indeed, they even get
    it wrong, claiming the number to be 1 x 10^65 (they also get the
    citation wrong, listing the date of Yockey's 1977 paper as 1981, and printing
    his actual 1981 article not as vol. 91, but as 191). Of course, even
    Yockey's other assumptions, such as regarding how many combinations could be
    self-replicating, are questionable. He argues for a 4-bit code. Yet
    he himself admits that replicating proteins are known that function on a
    3-bit code (p. 19), and he admits that, after all is said and done, a
    protein chain as large as 100,000 amino-acids long could be hit upon in the
    known age and expanse of the universe, if we assume a 2-bit
    proto-gene (p. 22). He argues against such a replicating system, however, but
    unconvincingly. His argument is that such a small code would require
    longer chains to accomplish the same results, but that is moot. All we need
    to get life going is anything that replicates, no matter how inefficiently or
    inaccurately, since all the failures will be washed away, no matter how many
    more there are, while the successes will remain and continue to
    reproduce. Then natural selection can get to work. And it is easy to imagine
    how a 2-bit replicator could chain with another in a symbiotic
    relationship, thereby giving rise to a 4-bit code like our present DNA
    system. Yockey does not even consider this scenario."

    Or see

    "However, an analysis by Ekland suggests that in the sequence space of 220
    nucleotide long RNA sequences, a staggering 2.5 x10112
        sequences are efficent ligases [12]. Not bad for a compound previously
    thought to be only structural. Going back to our primitive ocean
        of 1 x 1024 litres and assuming a nucleotide concentration of 1 x 10-7 M
    (23), then there is roughly 1 x 1049 potential nucleotide chains,
        so that a fair number of efficent RNA ligases (about 1 x 1034) could be
    produced in a year let alone a million years. The potential
        number of RNA polymerases is high also, about 1 in every 1020 sequences
    is an RNA polymerase [12]. Similar considerations apply
        for ribosomal acyl transferases, (about 1 in every 1015 sequences), and
    ribozymal nucleotide synthesis [1,6,13].

        Similarly, of the 1 x 10130 possible 100 unit proteins, 3.8 x 1061
    represent cytochrome C alone!![29]. There's lots of functional enyzmes
        in the peptide/nucleotide search space, so it would seem likely that a
    functioning ensemble of enzymes could be brewed up in an early
        Earths prebiotic soup. "

    Pruest: If God used only random processes and natural selection when He
    life 3.8 billion years ago, we should be able to successfully simulate
    it in a computer. You may even cheat: the genome sequences of various non-
    parasitic bacteria and archaea are available. The challenge stands. By
    grace alone we proceed, to quote Wayne.

    See for instance


    How do genetic systems gain information by evolutionary processes? Answering
    question precisely requires a robust, quantitative measure of information.
    fifty years ago Claude Shannon defined information as a decrease in the
    uncertainty of
    a receiver. For molecular systems, uncertainty is closely related to entropy
    and hence
    has clear connections to the Second Law of Thermodynamics. These aspects of
    information theory have allowed the development of a straightforward and
    method of measuring information in genetic control systems. Here this method
    is used
    to observe information gain in the binding sites for an artificial `protein'
    in a computer
    simulation of evolution. The simulation begins with zero information and, as
    naturally occurring genetic systems, the information measured in the fully
    binding sites is close to that needed to locate the sites in the genome. The
    transition is
    rapid, demonstrating that information gain can occur by punctuated


    Proc. Natl. Acad. Sci. USA, Vol. 97, Issue 9, 4463-4468, April 25, 2000
    Vol. 97, Issue 9, 4463-4468, April 25, 2000 Evolution of biological
    Christoph Adami*,, Charles Ofria,§, and Travis C. Collier¶

    " Abstract

    To make a case for or against a trend in the evolution of complexity in
    biological evolution, complexity needs to be both rigorously
    defined and measurable. A recent information-theoretic (but intuitively
    evident) definition identifies genomic complexity with the
    amount of information a sequence stores about its environment. We investigate
    the evolution of genomic complexity in populations
    of digital organisms and monitor in detail the evolutionary transitions that
    increase complexity. We show that, because natural
    selection forces genomes to behave as a natural "Maxwell Demon," within a
    fixed environment, genomic complexity is forced to increase. "


    "Conclusions. Trends in the evolution of complexity are difficult to argue
    for or against if there is no agreement on how to measure complexity. We
    have proposed here to identify the complexity of genomes by the amount of
    information they encode about the world in which they have evolved, a
    quantity known as "physical complexity" that, while it can be measured only
    approximately, allows quantitative statements to be made about the
    evolution of genomic complexity. In particular, we show that, in fixed
    environments, for organisms whose fitness depends only on their own
    sequence information, physical complexity must always increase. That a
    genome's physical complexity must be reflected in the structural complexity
    of the organism that harbors it seems to us inevitable, as the purpose of a
    physically complex genome is complex information processing, which can
    only be achieved by the computer which it (the genome) creates.

    That the mechanism of the Maxwell Demon lies at the heart of the complexity
    of living forms today is rendered even more plausible by the many
    circumstances that may cause it to fail. First, simple environments spawn
    only simple genomes. Second, changing environments can cause a drop in
    physical complexity, with a commensurate loss in (computational) function of
    the organism, as now meaningless genes are shed. Third, sexual
    reproduction can lead to an accumulation of deleterious mutations (strictly
    forbidden in asexual populations) that can also render the Demon
    powerless. All such exceptions are observed in nature.

    Notwithstanding these vagaries, we are able to observe the Demon's operation
    directly in the digital world, giving rise to complex genomes that,
    although poor compared with their biochemical brethren, still stupefy us with
    their intricacy and an uncanny amalgam of elegant solutions and clumsy
    remnants of historical contingency. It is in no small measure an awe before
    these complex programs, direct descendants of the simplest
    self-replicators we ourselves wrote, that leads us to assert that even in
    this view of life, spawned by and in our digital age, there is grandeur. "

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