The Cambrian Information Explosion – Part 2

Extracted from our series, The New Scientific Evidence That Points to the Existence of God, Part 3. Edited for publication.

Dr. John Ankerberg: In your book, you explain that there is a mathematical reason that a natural selection acting on random mutational changes in DNA will never generate new proteins and those major changes in life. Tell us about that.

Dr. Stephen Meyer: Right. Here’s an analogy that may help. If we think of an English word, say a 12-character word, it turns out that for every arrangement of those English letters, those 26 letters in the English alphabet that will spell a word, there’s a corresponding hundred trillion gibberish sequences. And that’s just because there are so many different ways you can arrange the letters—of 26 times 26 times 26 times 26 possibilities to the 12th power—that’s a lot of different combinations that you could generate.

Now, the question that many biologists started to ask, and mathematicians in the 1960s, was, does that same sort of problem apply to the information in DNA? What we know from English is there’s a lot more ways to go wrong in arranging letters than there are to go right, to build a functioning word. Is the same thing true of the DNA? Because if it is, then random mutations are going to be much more likely to degrade information than to build it.

And what has been discovered is that the DNA protein system of information storage and transmission is subject to this very same problem: that there are a lot more ways to arrange DNA characters that will produce nonfunctional gibberish, amino acid sequences that don’t fold into proteins, than there are that will produce stable protein folds that will perform functions. And the ratio is not just one in 100 trillion.

I have a colleague, Douglas Axe, who worked on this for 14 years at Cambridge University. And he asked a really important question. He said, how common or rare are the functional sequences in comparison to all the non-functional gibberish sequences? And what he discovered was that for a relatively short protein of about 150 amino acids long,…

Dr. John Ankerberg: Which is no big deal in your body.

Dr. Stephen Meyer: No big deal. We’ve got some that are thousands of amino acids long, so this is a relatively short protein. So the question Axe was asking is, for every one of these possible arrangements of amino acids, how many will fold into a stable protein structure that’s capable of doing a job? And the ratio that he determined experimentally was that for every stable protein structure that’s function ready, that’ll do a job, there are 10 to the 77th gibberish sequences of amino acids that won’t. Which means that, in essence, what we’re looking at is like a bike lock where you’ve got 10 possibilities at each dial and 77 dials. And you’re searching for one combination out of all those 10 to the 77th possible arrangements.

And it turns out if you do the math, which I do in the book, that even with all the organisms that ever existed on planet earth, and there are about 10 to the 40th organisms, which would give you 10⁴⁰ replication opportunities, where you could have a mutation that would search that big space, you still only could search a minuscule portion of the total number of possibilities. Which means it’d be kind of like looking at a, to change the metaphor a bit, it’d be like having a needle in a haystack search where you’ve got a needle hidden in a great big haystack, and you’re only allowed to search one tiny quadrant. The quadrant is 10⁴⁰ over 10⁷⁷, which is the fraction 1 over 10³⁷. Which is to say, you would only be allowed to search randomly in the entire history of life on earth, one 10 trillion trillion trillionth of the possible amino acid sequences.

Now, to just bring that point home, what that means is that the mutation selection mechanism, a random search, is overwhelmingly more likely to fail than to succeed. It’s overwhelmingly more likely to find a non-functional sequence than a functional one. Which means it’s not a plausible mechanism for generating new biological information. And that’s a big problem.

Continued in Part 3