The Optimality of the Genetic Code

General Academics Science, Technology and Medicine
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Errr, there is no list of parameters to test the optimality of the genetic code. However, a few have been tested so far. Look among the 9 points.

For the one parameter yes. It means by taking into consideration only one paramater, the code is very optimal and other codes could have emerged that are also very optimal and even more so with regards to that one parameter… error minimization. Use the information, don’t use it.

I did in the OP. Those are all the known parameters that I know of.

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We’re discussing this. Part of the discussion proses should be you giving straightforward answers to questions. I get the distinct feeling I am being led around the nose here. Sort of a vague sense of wtf. Now. Looking among the 9 parameters (how can there be 9 parameters now when you objected to this a second ago? How many are there?) we know at least one which gives a result that simply makes no sense to me ie it is optimal [whatever that really means] but it could have been more optimal and starting from any point will result in optimality (various forms thereof some better than others)

I asked you whether any of the other parameters have similar results which didn’t get me a clear answer.

Which result for which parameter stands out for you and why?

For the one parameter yes. It means by taking into consideration only one paramater, the code is very optimal and other codes could have emerged that are also very optimal and even more so with regards to that one parameter... error minimization. Use the information, don't use it.
How?
I did in the OP. Those are all the known parameters that I know of.
As oppose to unknown parameters that we don't know of? Okay. So we can have a list then? Of parameters, tested parameters and results?
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9 points, not 9 parameters… Like I said, there is no list of parameters to test the optimality of the genetic code. However, a few have been tested so far. And they are listed among the 9 points… not parameters.

What does optimal mean? An extract from article two explains the concept:

[b]The structure of the genetic code is manifestly nonrandom [3][/b]. Given that there are 64 codons for only 20 amino acids, most of the amino acids are encoded by more than one codon, i.e., the standard code is highly redundant; the two exceptions are methionine and tryptophan, each of which is encoded by a single codon. The codon series that code for the same amino acid are, with the single exception of serine, arranged in blocks in the code table and the corresponding codons differ only in the third base position, with the exceptions of arginine and leucine, for which the codon series differ in the first position (Fig. ​(Fig.1).1Figure 1). The importance of the nucleotides in the three codon positions dramatically varies: 69% of the point mutations in the third codon position are synonymous, only 4% of the mutations in the first position are synonymous, and none of the point mutations in the second position are synonymous. The structure of the code also, obviously, reflects physicochemical similarities between amino acids; e.g., all codons with a U in the second position code for hydrophobic amino acids (see Fig. ​Fig.11Figure 1 where the blocks of synonymous codons are colored with respect to the polar requirement scale [6] (PRS), which is a measure of hydrophobicity). The finer structure of the code comes into view if synonymous codon series that differ by purines or pyrimidines are compared [7]. Related amino acids show a strong tendency to be assigned related codons [3,4,8]. [b]Generally, the standard code is thought to conform with the principles of optimal coding, i.e., the structure of the code appears to be such that it is robust with respect to point mutations, translation errors, and shifts in the reading frame. The block structure of the code is considered to be a necessary condition of this robustness [9].[/b]

I don’t have an answer, you will have to find that out for yourself.

All of them are equally interesting at the moment.

I don’t know.

Errr, the OP is there for all to read. Everyone is welcome to extract what they want from it. try and add information as well. As is, I am not sure of all the parameters, and the OP post mentioned a few. You are going to have to dig up all the different parameters that have been tested. That requires a bit of effort and time and time is not exactly on my side now. But, if it makes you feel better, these articles should help you:

Early Fixation of an Optimal Genetic Code
Evolution of the genetic code: partial optimization of a random code for robustness to translation error in a rugged fitness landscape
The genetic code is nearly optimal for allowing additional information within protein-coding sequences
A Neutral Origin for Error Minimization in the Genetic Code.
Does codon bias have an evolutionary origin?
Optimality of the genetic code with respect to protein stability and amino-acid frequencies

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My bad. So we don’t know how many parameters or what an overall picture would give us. I see.

[b]Generally, the standard code is thought to conform with the principles of optimal coding, i.e., the structure of the code appears to be such that it is robust with respect to point mutations, translation errors, and shifts in the reading frame. The block structure of the code is considered to be a necessary condition of this robustness [9].[/b]
That’s cool. So we know for at least one parameter this is rather pointless. How about the other parameters which were tested?
I don't have an answer, you will have to find that out for yourself.
Is that the same as “I don’t know”? That would be rather weird, giving our history.
I don't know.
And that*is* an “I don’t know” answer, no doubt about it. I am flabbergasted and shocked to the core of my being. I always knew there are so many things you don’t know and yet it has been a complete mindboggling experience in futility to get you to admit to such. Here we have two in one post! What now? :o
Errr, the OP is there for all to read. Everyone is welcome to extract what they want from it. try and add information as well. As is, I am not sure of all the parameters, and the OP post mentioned a few. You are going to have to dig up all the different parameters that have been tested. That requires a bit of effort and time and time is not exactly on my side now. But, if it makes you feel better, these articles should help you:
No worries, I am in no rush here and would rather have you explain things to me than try and wallow through that sludge of information. I am still trying to get to grips on the whole concept of what this all means and I am sure I’ll get you to answer eventually, [b]even if it is a “I don’t know” answer[/b]. As you well know by now I have no problems with giving and accepting such. My problem has always and will always be with making shit up.
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Not really pointless. They discovered where on the fitness landscape the code is situated with respect to error minimization. Hardly pointless science there.

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I didn’t mean to imply the science is pointless. I’m sure research is ongoing and anything that adds to our knowledge is sweet.

For the purpose of our discussion here it merely seems that the implications are rather pointless, other than adding to what we know.

I was hoping for an understanding of why you made this very long post with all this heaps and heaps and heaps of information. Which I am finding some difficulty in discussing with you. I admit to some frustration with respects to that aspect.

Currently it seems weird, you made it to discuss it, but it doesn’t feel like you are discussing. Am I wrong?

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You are. The discussion seems to be stuck on 1 parameter.

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If that is true, I apologise. The reason may be that I found a website that easily explained in layman’s terms.

I have been hoping you’d do the same with the rest of dem parameters (however many there may be, which is currently still a mystery) and / or give us some conclusion or summary to further discussion.

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Welcome to share the link so that all can read it.

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I did. Page one, reply 11. You supplied it.

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Another interesting article:
Extreme genetic code optimality from a molecular dynamics calculation of amino acid polar requirement.
Abstract:

A molecular dynamics calculation of the amino acid polar requirement is used to score the canonical genetic code. Monte Carlo simulation shows that this computational polar requirement has been optimized by the canonical genetic code, an order of magnitude more than any previously known measure, effectively ruling out a vertical evolution dynamics. The sensitivity of the optimization to the precise metric used in code scoring is consistent with code evolution having proceeded through the communal dynamics of statistical proteins using horizontal gene transfer, as recently proposed. The extreme optimization of the genetic code therefore strongly supports the idea that the genetic code evolved from a communal state of life prior to the last universal common ancestor.
The conclusion:
In conclusion, earlier estimates of code optimality were understated by a statistically significant amount. The extent of optimality and its dependence on metric revealed here further support the notion that the genetic code must have evolved during an early communal state of life

Evolutionary pressure to optimize the genetic code seemed to have diminished soon after the emergence of the last universal common ancestor.

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Cite the paragraph in the paper that says that 'cos it looks a whole helluva lot like your usual conclusion jumping and fabrication. You know, where you pull a sterile gonad from your ass and call it a gemstone.