Darwinism vs. the real world IV

Computing the "Best Case" Probability of Proteins from Actual Data, and Falsifying a Prediction of Darwinism

Kirk Durston July 28, 2015 4:52 PM | 

 

 

Biological life requires thousands of different protein families, about 70 percent of which are "globular" proteins, with a three-dimensional shape that is unique to each family of proteins. An illustration is shown in the picture at the top of this post. This 3D shape is necessary for a particular biological function and is determined by the sequence of the different amino acids that make up that protein. In other words, it is not biology that determines the shape, but physics. Sequences that produce stable, functional 3D structures are so rare that scientists today do not attempt to find them using random sequence libraries. Instead, they use information they have obtained from reverse-engineering biological proteins to intelligently design artificial proteins.
Indeed, our 21st-century supercomputers are not powerful enough to crunch the variables and locate novel 3D structures. Nonetheless, a foundational prediction of neo-Darwinian theory is that a ploddingly slow evolutionary process consisting of genetic drift, mutations, insertions, and deletions must be able to "find" not just one, but thousands of sequences pre-determined by physics that will have different stable, functional 3D structures. So how does this falsifiable prediction hold up when tested against real data? As ought to be the case in science, I have made my program available so that you can run your own data and verify for yourself the kinds of probabilities these protein families represent.
This program can compute an upper limit for the probability of obtaining a protein family from a wealth of actual data contained in the Pfam database. The first step computes the lower limit for the functional complexity or functional information required to code for a particular protein family, using a method published by Durston et al. This value for I(Ex) can then be plugged into an equation published by Hazen et al. in order to solve the probability M(Ex)/N of "finding" a functional sequence in a single trial.
I downloaded 3,751 aligned sequences for the Ribosomal S7 domain, part of a universal protein essential for all life. When the data was run through the program, it revealed that the lower limit for the amount of functional information required to code for this domain is 332 Fits (Functional Bits). The extreme upper limit for the number of sequences that might be functional for this domain is around 10^92. In a single trial, the probability of obtaining a sequence that would be functional for the Ribosomal S7 domain is 1 chance in 10^100 ... and this is only for a 148 amino acid structural domain, much smaller than an average protein.
For another example, I downloaded 4,986 aligned sequences for the ABC-3 family of proteins and ran it through the program. The results indicate that the probability of obtaining, in a single trial, a functional ABC-3 sequence is around 1 chance in 10^128. This method ignores pairwise and higher order relationships within the sequence that would vastly limit the number of functional sequences by many orders of magnitude, reducing the probability even further by many orders of magnitude -- so this gives us a best-case estimate.
What are the implications of these results, obtained from actual data, for the fundamental prediction of neo-Darwinian theory mentioned above? If we assume 10^30 life forms with a fast replication rate of 30 minutes and a huge genome with a very high mutation rate over a period of 10 billion years, an extreme upper limit for the total number of mutations for all of life's history would be around 10^43. Unfortunately, a protein domain such as Ribosomal S7 would require a minimum average of 10^100 trials, about 10^57 trials more than the entire theoretical history of life could provide -- and this is only for one domain. Forget about "finding" an average sized protein, not to mention thousands.
As we all know from probabilities, you can get lucky once, but not thousands of times. This definitively falsifies the fundamental prediction of Darwinian theory that evolutionary processes can "find" functional protein families. A theory that has an essential prediction thoroughly falsified by the data should have no place in science.
Could natural selection come to the rescue? As we know from genetic algorithms, an evolutionary "search" will only work for hill-climbing problems, not for "needle in a haystack" problems. There are small proteins that require such low levels of functional information to perform simple binding tasks that they form a nice hill-climbing problem that can be easily located in a search. This is not the case, however, for the vast majority of protein families. As real data shows, the probability of finding a functional sequence for one average protein family is so low, there is virtually zero chance of obtaining it anywhere in this universe over its entire history -- never mind finding thousands of protein families.
What are the implications for intelligent design science? A testable, falsifiable hypothesis of intelligent design can be stated as follows:

A unique attribute of an intelligent mind is the ability to produce effects requiring a statistically significant level of functional information.

Given the above testable hypothesis, if we observe an effect that requires a statistically significant level of functional information, we can conclude there is an intelligent mind behind the effect. The average protein family requires a statistically significant level of functional, or prescriptive, information. Therefore, the genomes of life have the fingerprints of an intelligent source all over them.

 

A line in the sand XVIII

Tom Wolfe calls out the Darwinian Gestapo

In The New Yorker, Tom Wolfe Compares Persecution of Intelligent Design Advocates to the "Spanish Inquisition"

David Klinghoffer July 28, 2015 10:44 AM

How did we miss this? The comment is brief but pungent to say the least.Interviewed by The New Yorker earlier this year, the great novelist and journalist Tom Wolfe acknowledged that he's writing a book about evolution -- actually, "a history of the theory of evolution from the nineteenth century to the present." No indication of what his overall thesis might be, but he "invokes the Spanish Inquisition when discussing how academics have cast out proponents of intelligent design for 'not believing in evolution the right way.'"

The metaphor is apt, since the Spanish Inquisition was all about rooting out people who held the wrong beliefs in secret. The expulsion of the Jews from Spain in 1492 had already pushed out anyone openly professing Judaism. It was converted Jews, claiming to be loyal to the dominant faith, who were the focus of the inquisitors.

No metaphor is an exact equation between two things -- it wouldn't be a metaphor if it were. But uncovering and punishing those with secret sympathies for ID is indeed a priority for zealous evolutionists, who insist everyone needs to believe in evolution in "the right way." The anxiety this provokes, especially in academia, is something we deal with all the time behind the scenes.

I don't have any idea what view Wolfe takes on ID other than his obviously deploring such intimidation. But we noted a while back that he was seen in the audience when Eric Metaxas interviewed Stephen Meyer about Darwin's Doubt at the Union League Club. It was already known then that Wolfe was writing a book called The Human Beast.

His attitudes are now slowly coming into focus, demonstrating once again the Thomas Nagel Principle, aka the Tom Stoppard Rule: when you reach a certain level of fame and accomplishment, if you are independent-minded, you can say whatever you want without fear. Which in turn gives courage to others lacking your bullet-proof armor. This, I predict, is going to be good.