This is strange, you simply dismiss a (real) peer reviewed paper in a respectable journal, and reply with a blog post from a blogger we know nothing about.
Which is going to be more out on a limb?
But if we look at what Boammaaruri does, it is exactly the same as what the DI does, it takes Axe's 2004 paper
“Estimating the Prevalence of Protein Sequences Adopting Functional Enzyme Folds”, and it takes the 1 in 10(77) figure from that paper, then that figure is extrapolated to every protein in existence, and voila evolution is not possible.
Do you really think we can do that?
Well to find out, let us concentrate on Axe's 2004 paper, which is an actual peer reviewed one, unlike the ones published in BIO-complexity, let's take a look at what it actually says.
Does this paper allow for such a broad generalization?
Well according to
this essay, it does not.
It summarizes:
Summary
To summarize, the claims that have been and will be made by ID proponents regarding protein evolution are not supported by Axe’s work. As I show, it is not appropriate to use the numbers Axe obtains to make inferences about the evolution of proteins and enzymes. Thus, this study does not support the conclusion that functional sequences are extremely isolated in sequence space, or that the evolution of new protein function is an impossibility that is beyond the capacity of random mutation and natural selection.
So, the whole “Hard-to-Get-a-Protein” hypothesis (HGP for short, a term i borrow from this essay:
Is it easy to get a new protein?) rest on the assumption that a Axe's estimate for one very specific protein, under very specific, and specially selected, experimental circumstances, is valid for the evolution of any new protein.
Further, given that the HGP hypothesis is a negative argument (it is impossible that...), it is extremely sensitive for any positive arguments for the opposite.
And if we look for scientific evidence for that, it is not that hard to find.
For instance
the paper that you dismissed one one aspect:
In your link, they got a really low estimate of 10^10 by assuming that amino acids could be coarsely grouped into hydrophilic ones and hydrophobic ones! Well, I am sure you could reduce the number of amino acids slightly (if starting life all over again), but those amino acids vary in a whole variety of ways - for example their bulk, and whether they contain SH groups etc. The shape of the amino acids is critical because the protein has to fold twice, to become active (there may be exceptions, I don't know).
David
While i have to admit that a lot of these papers go partially over my head, the coarsely grouping amino acids into hydrophilic and hydrophobic ones, is only one suggestion to reduce sequence space, if i understand correctly.
For instance the suggestion that folds with fewer amino acids form scaffolds capable of supporting all protein functions :
The assumption that a protein chain needs to be at least 100 amino acids in length also rather inflates the size of sequence space when it is known that many proteins are modular and contain domains of as few as approximately 50 amino acids thereby reducing the space to 2050or approximately 1065 (e.g.
Sobolevsky & Trifonov 2006). The conclusion from all of these coarse-graining approaches is that a reduced alphabet of amino acids is quite capable of producing all protein folds (approx. a few thousand discrete folds;
Denton 2008) and providing a scaffold capable of supporting all protein functions
Or:
that the actual identity of most of the amino acids in a protein is irrelevant. An example in nature could be the prokaryotic DNA methyltransferases which each contain a target recognition domain (TRD) of approximately 150 amino acids that recognizes specific DNA sequences usually of 3–6 bp in length, and a conserved catalytic domain. The thousands of known TRD sequences show negligible amino acid sequence conservation despite the rather limited number of nucleotide sequences they are required to recognize.
More evidence for a more navigable sequence space:
Functional proteins from a random-sequence library
In conclusion, we suggest that functional proteins are suf®ciently common in protein sequence space (roughly 1 in 1011) that they may be discovered by entirely stochastic means, such as presumably operated when proteins were ®rst used by living organisms. However, this frequency is still low enough to emphasize the magnitude of the problem faced by those attempting de novo protein design.
Simple evolutionary pathways to complex proteins
In summary, the conclusions derived from the current study are based on a model that is quite restrictive with respect to the requirements for the establishment of new protein functions, and this very likely has led to order-of-magnitude underestimates of the rate of origin of new gene functions following duplication. Yet, the probabilities of neofunctionalization reported here are already much greater than those suggested by Behe and Snoke. Thus, it is clear that conventional population-genetic principles embedded within a Darwinian framework of descent with modification are fully adequate to explain the origin of complex protein functions.
Another interesting read:
Exploring protein fitness landscapes by directed evolution
Despite the vast size of sequence space and the complex nature of protein function, the Darwinian algorithm of mutation and selection provides a powerful method to generate proteins with altered functions. This simple uphill walk on a fitness landscape in sequence space works because proteins are wonderfully evolvable and can adapt to new conditions or even take on new functions with only a few mutations.
And even more positive evidence against the HGP hypothesis comes from examples of evolution in action.
As there are the appearance of
Nylonase, and the
E. coli long-term evolution experiment
So to conclude, in my opinion, the HGP hypothesis being a negative argument, can only work if it would have to deal with known facts. To prove a negative it would have to be only vulnerable to unknown unknown's.
For instance, an object with mass can not hover against gravity, unaided by an external energy source pushing against it. To claim that statement wrong we would have to show new information, information that we now do not even know we lack.
The HGP hypothesis is not only vulnerable to unknown unknowns, it is also vulnerable to known unknowns, and to known facts.
As i think is shown, with the positive evidence for a smaller sequence space with easier pathways to functional proteins, the HGP hypothesis fails.
I would agree that the estimates for size of protein space, and the chance of getting a functional protein, are completely open for (reasonable) discussion.
But that is not the argument that the DI is making, they stick to their 1 in 10(77) figure, which is at the most extreme, in the light of the other evidence, the implausible end of the spectrum.
So i ask you, David, do you think the DI will ever let that figure go, will "evolution news" ever publish a blog post that says "in light of recent scientific evidence, we were wrong on that 1 in 10(77) thing"?
Edit: another good read:
How do new proteins arise?
Conclusions
We have reviewed here recent insights on how new
proteins emerge. We suggest the number of newly arising
proteins, for example from intergenic regions, is very
small and unlikely to be a major driving force in organismic
evolution. The underlying reason may be that
forming functional proteins or transforming structures
into each other is very difficult, albeit not impossible.
Latent traits, multistable bridge structures and disordered
regions seem to play a major role in transitions and
certainly deserve further attention for specific experiments.
Rearrangements of domains are frequent and
can be seen as a way to circumvent the tight biophysical
constraints imposed on protein evolution. Current
research indicates that rearrangements are frequent and
follow a random model [8]. Thus rearrangements can be
seen as a ‘higher level’ form of neutral evolution: it allows
for the exploration of ‘rearrangement space’, which is
reminiscent of the concept of neutral exploration of
sequence space by point mutations, until rare beneficial
‘mutations’ (arrangements) become fixed.