How many human MYH7 alleles exist, Bill?
This has nothing to do with the LUCA hypothesis. God could have created humans 6000 years ago and this number would still be relevant to the claim that function is rare in sequence space.
Why are IDcreationists so afraid of the actual data?
An example of new is the spliceosome where there is little homology in prokaryotic cells. Unique is performing a new function like splicing inside a cell nucleus.
Thatâs arithmetic. What are your assumptions?
Iâm not just being obtuse, this is important.
The assumption is that Francis Crick was right and DNA/Proteins are chemical sequences. There is 60 years of data supporting this hypothesis.
Good start, but you can do better. What process governs the formation of new alleles? (Random yes, but random in what way?)
Those are not definitions of ânewâ and âuniqueâ. Define both terms please?
@colewd is an intuitive thinker, which sometimes leads him to skip ahead of himself in his thought process. I tend to do the same thing myself. Itâs not a bad trait in itself, but you need to take a step back for a hard look at those intuitive leaps to make sure it is supported. 
You are charitable to a fault. And I mean that literally.
No, your assumption is that function is far less prevalent in sequence space than we know it to be. Your assumption is contradicted by the objective data. At some level, you agree; otherwise youâd be examining the data for yourself.
Yeah, I know. Iâm an optimist and sometimes I get burned for it, but thatâs how I roll.
And that is connected to your equation⌠how?
Why do you think this assumption is required? How much function is there across all the diverse set of proteins?
[quote=âcolewd, post:174, topic:14095â]
Required? Iâm pointing out that the assumption you are using is objectively false and you appear to lack the curiosity required to correct it.
Thatâs completely irrelevant to the validity of your assumption. Try not to change the subject, Bill.
Let me stop you right there.
My assumptions come from a collection of empirical data. The data you have offered is generally from a couple of sources and I have looked at the data you have provided.
I think you need to take a wider look at the issues. How exactly does the amount of alleles in myosin point to evolvability of proteins. Does this really widen the range of function in protein space that is generally accepted by the literature?
No they donât. You canât cite a single reference detailing empirical evidence that supports your assumptions.
I donât see a speck of evidence to support that claim. If you disagree, tell us about the âempiricalâ aspect of those data.
I donât see any evidence to suggest that you have looked at anything Iâve offered.
I think youâre hilarious, given that Iâve spent decades studying how sequence variation changes protein function. Youâre the layman taking the narrowest look you can to support what you wish was true.
Weâre not even to any estimate of evolvability. Weâre stuck on you not having any evidence to support your assumptions about the simple prevalence of function in sequence space.
You havenât even looked at this particular myosin, because your use of âalleles in myosinâ obviously shows that you donât realize that there are very many myosins.
This particular cardiac and slow-twitch skeletal myosin heavy chain is a good one to consider because:
But what are they!? You still havenât said!
I agree with @Art statement that there is a range of function in sequence space depending on how you measure it and the function itself.
From his 2007 paper:
That is the real question that Axe, ID proponents, and other who follow this sort of discussion would ask. To get some idea, we can turn to Axeâs paper. Axe mentions two other studies â one deals with experiments done with the lambda repressor, and the other with chorismate mutase. Work with the lambda repressor (Reidhaar-Olson and Sauer, 1990) yielded a âvalueâ for the frequency of functional variants of 1 in 10^63 (roughly) for the 92-mer. Work with chorismate mutase (Taylor et al., PNAS 98, 10596-10601, 2001) gave a value of 1 in 10^24 for the 93 amino acid enzyme. Scaled for a similar size protein, Axeâs work gives a value of 1 in 10^59, which falls within the range established by previous work. (The literature in this area is rather large, far beyond the scope of this article to review. Suffice to say that the range of âprobabilityâ stated here is representative of the numerous studies in this area.)
You mean:
What is interesting is that the forward approach typically yields a âsuccess rateâ in the 10^-10 to 10^-15 range â one usually need screen between 10^10 â 10^15 random sequences to identify a functional polymer. This is true even for mRNA display. These numbers are a direct measurement of the proportion of functional sequences in a population of random polymers, and are estimates of the same parameter â density of sequences of minimal function in sequence space â that Axe is after.
So you agree that the range of functionality in random sequences is 10^-12 (give or take a couple orders of magnitude). Thatâs within the scope of biological systems.
Although Iâm personally inclined to say that you still havenât provided any actual assumptions. Youâve vaguely suggested at something one assumption might be, but it isnât my job to guess. Also, Iâve been asking about the relevance of the provided equation to your assumptions, and this comment certainly does nothing to answer that.
So keep trying.