In a message dated 9/22/2000 4:50:01 AM Pacific Daylight Time,
pruest@pop.dplanet.ch writes:
<< But let's look more closely at what really happens in evolution! Hubert
P.
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
organisms.
He found that 27 of the 101 amino acid positions were completely
invariant,
2 different amino acids occurred at 14 positions, 3 at 21, etc., more
than
10 nowhere. Optimistically assuming that the 101 positions are mutually
independent and that chemically similar amino acids can replace each
other
at the variable positions without harming the enzymatic activity, he
calculated that 4 x 10^61 different sequences of 101 amino acids might
have
cytochrome c activity. But this implies that the probability of
spontaneous
emergence of any one of them is only 2 x 10^(-65), which is way too low
to
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
of
life, may be expected to have much less activity and to be much less
sensitive to variation. Unfortunately, before someone synthesizes a set
of
"primitive" cytochromes c, we have no way of knowing the effects of
these
factors.
>>
Is this what "really happens in evolution"? Laurie Godfrey in "Scientists
confront creationism" pp. 89 addresses Yockey and shows the flaws in his
calculations.
Or see http://www.infidels.org/library/modern/richard_carrier/addendaB.html
"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
replicating
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 http://www.talkorigins.org/faqs/abioprob.html
"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
created
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 http://www-lecb.ncifcrf.gov/~toms/paper/ev/
ABSTRACT
How do genetic systems gain information by evolutionary processes? Answering
this
question precisely requires a robust, quantitative measure of information.
Fortunately,
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
practical
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
in
naturally occurring genetic systems, the information measured in the fully
evolved
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
equilibrium.
Or
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
complexity
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. "
and
"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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