It is the area of science that studies the signs of intelligence.
Intelligent agents produce artifacts that other intelligent agents can recognize as the products of intelligence.
These artifacts may include:
1. Complex information
AND/OR
2. Multiple parts functioning together which have an irreducible core.
Wednesday, December 15, 2010
Sunday, October 17, 2010
Shortcuts to new protein folds.
There are some possible shortcuts.
1. The changes that are known to occur which change how specific an enzyme is for a particular reaction thus allowing it to use a slightly different chemical.
These are where a small change in the structure of an existing protein means that it can use a slightly altered substrate.
Examples of this kind of change are the oscillations in the antibiotics battle.
People discover an antibiotic --> microbes die
a microbe develops resistance by a small change in protein structure --> people die
People develop a slightly changed antibiotic --> microbes die.
Etc.
In these cases there is a shortcut to other similar functions by a relatively small number of mutations.
(Usually it is this kind of change that is presented as evidence for evolution.)
Why aren’t this kind of shortcuts sufficient to reassure us that evolution can solve the problem?
Not all proteins have this kind of relationship with each other. Protein databases have 1777 classes of structural domains These are the “superfamilies” of protein structures. There may be recognisable similarities between domains within a superfamily … but the superfamilies themselves are not related.
Even if all the proteins within a superfamily can be derived from one original sequence this does not explain the origin of all the 1777 plus classes of superfamily.
2. If a relatively few changes causes a change in function and this is followed by subsequent sequence divergence in the new protein. Axe considers an example of this from PA Alexander published in PNAS….. and argues that this will not get us very far.
3. If proteins are made up of a relatively small set of “chunks” rather like a lego kit. This would simplify the problem of building a new protein superfamily. Gene fusion events can be used to build a new structure.
But Axe states that…”The binding interfaces by which elements of secondary structure combine to become units of tertiary structure are predominantly sequence dependent, and therefore not generic.”
Thus enzymes with an identical function and 50% sequence similarity do not have chunks which are interchangeable. Even when this similarity is increased to 90% equivalent chunks are not interchangeable. Graziano and his co-workers constructed and tested a huge library of 10^8 variants of gene segments and found none that formed a folded structure.
Axe concludes that all of these putative shortcuts are dead ends. The Darwinian search mechanism is not capable of finding new protein folds by random sampling and all the shortcuts to new folds are dead ends.
1. The changes that are known to occur which change how specific an enzyme is for a particular reaction thus allowing it to use a slightly different chemical.
These are where a small change in the structure of an existing protein means that it can use a slightly altered substrate.
Examples of this kind of change are the oscillations in the antibiotics battle.
People discover an antibiotic --> microbes die
a microbe develops resistance by a small change in protein structure --> people die
People develop a slightly changed antibiotic --> microbes die.
Etc.
In these cases there is a shortcut to other similar functions by a relatively small number of mutations.
(Usually it is this kind of change that is presented as evidence for evolution.)
Why aren’t this kind of shortcuts sufficient to reassure us that evolution can solve the problem?
Not all proteins have this kind of relationship with each other. Protein databases have 1777 classes of structural domains These are the “superfamilies” of protein structures. There may be recognisable similarities between domains within a superfamily … but the superfamilies themselves are not related.
Even if all the proteins within a superfamily can be derived from one original sequence this does not explain the origin of all the 1777 plus classes of superfamily.
2. If a relatively few changes causes a change in function and this is followed by subsequent sequence divergence in the new protein. Axe considers an example of this from PA Alexander published in PNAS….. and argues that this will not get us very far.
3. If proteins are made up of a relatively small set of “chunks” rather like a lego kit. This would simplify the problem of building a new protein superfamily. Gene fusion events can be used to build a new structure.
But Axe states that…”The binding interfaces by which elements of secondary structure combine to become units of tertiary structure are predominantly sequence dependent, and therefore not generic.”
Thus enzymes with an identical function and 50% sequence similarity do not have chunks which are interchangeable. Even when this similarity is increased to 90% equivalent chunks are not interchangeable. Graziano and his co-workers constructed and tested a huge library of 10^8 variants of gene segments and found none that formed a folded structure.
Axe concludes that all of these putative shortcuts are dead ends. The Darwinian search mechanism is not capable of finding new protein folds by random sampling and all the shortcuts to new folds are dead ends.
Sunday, September 26, 2010
The Origin of Protein folds
Just trying to simplify the arguments of Axe in his review paper...
If we take E.coli as our model then the average length of a functional protein is around 300 amino acids.
If the protein is longer or if a number of different proteins are required to act in concert then the problem is made worse.
The number of possible sequences to be sampled to find functional proteins of this moderate size is vast...
There are two ways of reducing the sparse sampling problem.
(a) The number of possible sequences with a particular function is very large. Sequence space is rich in function.
(b) The functional sequences are in some way linked- once you have one function it is easy to jump to the next.
Axe argues that experimental results indicate that (a) is not big enough to solve the sparse search problem....
I will look at what he says about (b) next week!
If we take E.coli as our model then the average length of a functional protein is around 300 amino acids.
If the protein is longer or if a number of different proteins are required to act in concert then the problem is made worse.
The number of possible sequences to be sampled to find functional proteins of this moderate size is vast...
There are two ways of reducing the sparse sampling problem.
(a) The number of possible sequences with a particular function is very large. Sequence space is rich in function.
(b) The functional sequences are in some way linked- once you have one function it is easy to jump to the next.
Axe argues that experimental results indicate that (a) is not big enough to solve the sparse search problem....
I will look at what he says about (b) next week!
Tuesday, August 17, 2010
The Case Against a Darwinian Origin of Protein Folds
One of the paragraphs from the conclusion of Douglas Axe's recent article:
Clearly, if this conclusion (A dawinian search is insufficient to find new protein folds) is correct it calls for a serious rethink of how we explain protein origins, and that means a rethink of biological origins as a whole. Drawing on some of the points developed here, I presented an earlier version of this case several years ago to two prominent experts in the field. Bothered by my conclusion, both felt that it must be in error. When the three of us met for a discussion, they had their own hunches about where my reasoning might have gone wrong. Interestingly, though, after perhaps two hours of heated discussion neither agreed with the other’s hunch, and we ended up at a polite but dissatisfying impasse. I left with the distinct impression that my conclusion was being rejected not because it was unfounded but because it was unwelcome.
Sunday, June 13, 2010
Is intelligent design a possible cause of the origin of biological information?
In his 7th chapter Meyer discusses the nature of “historical sciences” such as geology and paleontology and evolutionary biology and argues that they use different methods to “experimental sciences” such as physics and chemistry.
He states that Stephen Jay Gould accepted this distinction and argued that historical scientific theories were testable by analysing their “explanatory power” (Gould, “Evolution and the Triumph of Homology”) Gould describes the process of testing in historical sciences as seeking “consilience”. Consilience is the situation where many facts can be explained well by a single proposition or theory.
Gould argues that historical sciences depend upon the knowledge of the laws of nature to make inferences about the past.
Meyer then asks whether a design hypothesis can be formulated as a historical scientific theory about what happened in the past.
Historical scientists cite the occurrence of an event or series of events in the past as the explanation for some observable phenomenon in the present.
Historical scientists use a distinctive mode of reasoning. Using their knowledge of cause and effect relationships historical scientists “calculate backwards” and infer past conditions and causes from present conditions and causes.
This type of reasoning is called “abductive” reasoning as opposed to inductive (in which a universal law is established from repeated observations) or deductive (in which a particular fact is deduced by applying a general law to another particular case.
Abductive logic was first described by Charles Sanders Pierce.
Despite the tentative nature of abductive reasoning we do make conclusive inferences about the past.
A conclusion of abductive reasoning is certain if we cannot explain the currently observed facts without the past cause.
An abductive conclusion is established by showing that it is either the best or the only explanation of the effects in question.
To address this problem in geology Thomas Chamberlain proposed a method of “multiple working hypotheses. This is also known as “inference to the best explanation”
Peter Lipton is associated with this way of reasoning arguing that it is used both in science and ordinary life. Discovering certain particular marks in fresh snow we infer that a person with snow shoes has passed this way. Lipton argued that the ability to explain particular facts sometimes mattered more than predictive success in the evaluation of a particular hypothesis.
The problem with this method of assessing explanations is exactly how we judge which is the best explanation as opposed to the explanation we like the best.
What makes an explanation the best?
1. A good explanation is causal.
2. A good explanation for a particular event is something which provides a “causal difference” in the outcome.
Historical scientists use the principle of causal adequacy. Causes that are known to produce the effect in question are better explanations. Charles Lyell expressed this as – “explanation of the past by causes now in operation.” Michael Scriven described this method as “retrospective causal analysis.” The candidate cause must provide independent evidence showing itself able to produce this effect on other occasions.
When there is only one possible cause for a particular effect the solution to the problem of what really happened is easy. This situation is where historical scientists can infer a uniquely plausible cause. For example an archaeologist who knows that scribes are the only known cause of linguistic inscriptions will, when they find a tablet containing ancient writing infer scribal activity. Where a particular past cause is known to be necessary to produce a subsequent effect, the occurrence of the effect is taken as sufficient to establish the occurrence of the cause.
Where there is more than one possible cause the situation is more difficult. In this case scientists will look for additional evidence that can help distinguish the explanatory power of the remaining explanations. They will look for additional facts for which there is only one adequate causal explanation. In practice the process of determining the best explanation involves examining a list of possible hypotheses. These will be compared for their known causal powers against the relevant evidence and then, like a detective, the scientist will progressively eliminate inadequate explanations until only one is left.
A second way of addressing this problem is to ask which of the adequate causes was actually present at the time of the event in question. Thus two criteria are needed:
1. causal adequacy
2. causal existence
To meet the second criteria historical scientists must show that the proposed cause is not only able to produce the event in question but that it was actually present at the right time and in the right place.
There are two ways of doing this
1. Showing the presently acting course must have been present in the past because this cause is the only known cause of the effect in question.
2. By examining a wider class of facts to show that only one other possible cause explains the whole collection.
Michael Scriven summarises situation. To establish a causal claim a historical scientist
1. needs to show that his proposed cause was present
2. that his proposed cause able to produce the effect under study
3. there is an absence of evidence of other possible causes.
Many scholars think that Charles Darwin structured his argument in the Origin to show that natural selection was both causally adequate and had causal existence. His theory of universal common descent could not be tested by predicting future outcomes under controlled experimental conditions. It could be demonstrated to be right by showing that it could explain already known facts in a more adequate fashion.
The question is now whether a case for an intelligent cause can be formulated and justified in this way. Is intelligent design a possible historical scientific explanation for the origin of biological information? Is it possible to formulate a case for intelligent design as an inference to the best explanation for the origin of biological information?
It is possible to conceive of the purposeful acts of an intelligent agent is a causal event. This clearly represents a known and presently acting adequate cause for the origin of information.
Our uniform and repeated experience indicates that intelligent agents produce information rich systems.
What causes now in operation produce digital code or specified information? Is there a known cause of the origin of such information? What does our uniform experience tell us?
Intelligent design must qualify at least as a possible scientific explanation for the origin of biological information.
Is intelligent design the only known or adequate cause of the origin specified information? If so then the past action of designing intelligence will be established as the strongest and most logically compelling form of historical inference.
He states that Stephen Jay Gould accepted this distinction and argued that historical scientific theories were testable by analysing their “explanatory power” (Gould, “Evolution and the Triumph of Homology”) Gould describes the process of testing in historical sciences as seeking “consilience”. Consilience is the situation where many facts can be explained well by a single proposition or theory.
Gould argues that historical sciences depend upon the knowledge of the laws of nature to make inferences about the past.
Meyer then asks whether a design hypothesis can be formulated as a historical scientific theory about what happened in the past.
Historical scientists cite the occurrence of an event or series of events in the past as the explanation for some observable phenomenon in the present.
Historical scientists use a distinctive mode of reasoning. Using their knowledge of cause and effect relationships historical scientists “calculate backwards” and infer past conditions and causes from present conditions and causes.
This type of reasoning is called “abductive” reasoning as opposed to inductive (in which a universal law is established from repeated observations) or deductive (in which a particular fact is deduced by applying a general law to another particular case.
Abductive logic was first described by Charles Sanders Pierce.
Despite the tentative nature of abductive reasoning we do make conclusive inferences about the past.
A conclusion of abductive reasoning is certain if we cannot explain the currently observed facts without the past cause.
An abductive conclusion is established by showing that it is either the best or the only explanation of the effects in question.
To address this problem in geology Thomas Chamberlain proposed a method of “multiple working hypotheses. This is also known as “inference to the best explanation”
Peter Lipton is associated with this way of reasoning arguing that it is used both in science and ordinary life. Discovering certain particular marks in fresh snow we infer that a person with snow shoes has passed this way. Lipton argued that the ability to explain particular facts sometimes mattered more than predictive success in the evaluation of a particular hypothesis.
The problem with this method of assessing explanations is exactly how we judge which is the best explanation as opposed to the explanation we like the best.
What makes an explanation the best?
1. A good explanation is causal.
2. A good explanation for a particular event is something which provides a “causal difference” in the outcome.
Historical scientists use the principle of causal adequacy. Causes that are known to produce the effect in question are better explanations. Charles Lyell expressed this as – “explanation of the past by causes now in operation.” Michael Scriven described this method as “retrospective causal analysis.” The candidate cause must provide independent evidence showing itself able to produce this effect on other occasions.
When there is only one possible cause for a particular effect the solution to the problem of what really happened is easy. This situation is where historical scientists can infer a uniquely plausible cause. For example an archaeologist who knows that scribes are the only known cause of linguistic inscriptions will, when they find a tablet containing ancient writing infer scribal activity. Where a particular past cause is known to be necessary to produce a subsequent effect, the occurrence of the effect is taken as sufficient to establish the occurrence of the cause.
Where there is more than one possible cause the situation is more difficult. In this case scientists will look for additional evidence that can help distinguish the explanatory power of the remaining explanations. They will look for additional facts for which there is only one adequate causal explanation. In practice the process of determining the best explanation involves examining a list of possible hypotheses. These will be compared for their known causal powers against the relevant evidence and then, like a detective, the scientist will progressively eliminate inadequate explanations until only one is left.
A second way of addressing this problem is to ask which of the adequate causes was actually present at the time of the event in question. Thus two criteria are needed:
1. causal adequacy
2. causal existence
To meet the second criteria historical scientists must show that the proposed cause is not only able to produce the event in question but that it was actually present at the right time and in the right place.
There are two ways of doing this
1. Showing the presently acting course must have been present in the past because this cause is the only known cause of the effect in question.
2. By examining a wider class of facts to show that only one other possible cause explains the whole collection.
Michael Scriven summarises situation. To establish a causal claim a historical scientist
1. needs to show that his proposed cause was present
2. that his proposed cause able to produce the effect under study
3. there is an absence of evidence of other possible causes.
Many scholars think that Charles Darwin structured his argument in the Origin to show that natural selection was both causally adequate and had causal existence. His theory of universal common descent could not be tested by predicting future outcomes under controlled experimental conditions. It could be demonstrated to be right by showing that it could explain already known facts in a more adequate fashion.
The question is now whether a case for an intelligent cause can be formulated and justified in this way. Is intelligent design a possible historical scientific explanation for the origin of biological information? Is it possible to formulate a case for intelligent design as an inference to the best explanation for the origin of biological information?
It is possible to conceive of the purposeful acts of an intelligent agent is a causal event. This clearly represents a known and presently acting adequate cause for the origin of information.
Our uniform and repeated experience indicates that intelligent agents produce information rich systems.
What causes now in operation produce digital code or specified information? Is there a known cause of the origin of such information? What does our uniform experience tell us?
Intelligent design must qualify at least as a possible scientific explanation for the origin of biological information.
Is intelligent design the only known or adequate cause of the origin specified information? If so then the past action of designing intelligence will be established as the strongest and most logically compelling form of historical inference.
Sunday, May 23, 2010
Is ID Science?
This is not a simple or straight forward question. It is the question that Meyer addresses in his 7th chapter. I think I found this the most difficult chapter in the book.
Meyer discusses the nature of “historical sciences” such as geology and paleontology and evolutionary biology and argues that they use different methods to “experimental sciences” such as physics and chemistry. He states that Stephen Jay Gould accepted this distinction and argued that historical scientific theories were testable by analysing their “explanatory power” (Gould, “Evolution and the Triumph of Homology”) Gould describes the process of testing in historical sciences as seeking “consilience”. Consilience is the situation where many facts can be explained well by a single proposition or theory. Gould he says argues that historical sciences depend upon the knowledge of the laws of nature to make inferences about the past.
Meyer then asks whether a design hypothesis can be formulated as a historical scientific theory about what happened in the past.
Historical scientists cite the occurrence of an event or series of events in the past as the explanation for some observable phenomenon in the present. Historical scientists use a distinctive mode of reasoning. Using their knowledge of cause and effect relationships historical scientists “calculate backwards” and infer past conditions and causes from present conditions and causes.
This type of reasoning is called “abductive” reasoning as opposed to inductive(in which a universal law is established from repeated observations) or deductive (in which a particular fact is deduced by applying a general law to another particular case. Abductive logic was first described by Charles Sanders Pierce
Despite the tentative nature of abductive reasoning we do make conclusive inferences about the past.
A conclusion of abductive reasoning is certain if we cannot explain the currently observed facts without the past cause. An abductive conclusion is established by showing that it is either the best or the only explanation of the effects in question.
To address this problem in geology Thomas Chamberlain proposed a method of “multiple working hypotheses. This is also known as “inference to the best explanation”
Peter Lipton is associated with this way of reasoning arguing that it is used both in science and ordinary life. Discovering certain particular marks in fresh snow we infer that a person with snow shoes has passed this way. Lipton argued that the ability to explain particular facts sometimes mattered more than predictive success in the evaluation of a particular hypothesis.
The problem with this method of assessing explanations is exactly how we judge which is the best explanation as opposed to the explanation we like the best.
Meyer discusses the nature of “historical sciences” such as geology and paleontology and evolutionary biology and argues that they use different methods to “experimental sciences” such as physics and chemistry. He states that Stephen Jay Gould accepted this distinction and argued that historical scientific theories were testable by analysing their “explanatory power” (Gould, “Evolution and the Triumph of Homology”) Gould describes the process of testing in historical sciences as seeking “consilience”. Consilience is the situation where many facts can be explained well by a single proposition or theory. Gould he says argues that historical sciences depend upon the knowledge of the laws of nature to make inferences about the past.
Meyer then asks whether a design hypothesis can be formulated as a historical scientific theory about what happened in the past.
Historical scientists cite the occurrence of an event or series of events in the past as the explanation for some observable phenomenon in the present. Historical scientists use a distinctive mode of reasoning. Using their knowledge of cause and effect relationships historical scientists “calculate backwards” and infer past conditions and causes from present conditions and causes.
This type of reasoning is called “abductive” reasoning as opposed to inductive(in which a universal law is established from repeated observations) or deductive (in which a particular fact is deduced by applying a general law to another particular case. Abductive logic was first described by Charles Sanders Pierce
Despite the tentative nature of abductive reasoning we do make conclusive inferences about the past.
A conclusion of abductive reasoning is certain if we cannot explain the currently observed facts without the past cause. An abductive conclusion is established by showing that it is either the best or the only explanation of the effects in question.
To address this problem in geology Thomas Chamberlain proposed a method of “multiple working hypotheses. This is also known as “inference to the best explanation”
Peter Lipton is associated with this way of reasoning arguing that it is used both in science and ordinary life. Discovering certain particular marks in fresh snow we infer that a person with snow shoes has passed this way. Lipton argued that the ability to explain particular facts sometimes mattered more than predictive success in the evaluation of a particular hypothesis.
The problem with this method of assessing explanations is exactly how we judge which is the best explanation as opposed to the explanation we like the best.
What is the relationship of ID to Science? Is it Science?
Image from here
In his sixth chapter of “Signature in the Cell” Meyer presents the view that the scientific enterprise is much wider than “doing experiments.”
Kekule famously “discovered” the structure of benzene while having a daydream about snakes seizing their own tails.
I turned my chair to the fire [after having worked on the problem for some time] and dozed. Again the atoms were gamboling before my eyes. This time the smaller groups kept modestly to the background. My mental eye, rendered more acute by repeated vision of this kind, could not distinguish larger structures, of manifold conformation; long rows, sometimes more closely fitted together; all twining and twisting in snakelike motion. But look! What was that? One of the snakes had seized hold of its own tail, and the form whirled mockingly before my eyes. As if by a flash of lighting I awoke... Let us learn to dream, gentlemen.
Meyer uses the example of Watson and Crick who relied on other people’s experimental results and their own model building to present the structure of DNA. Once they had the idea…it was obviously right!
Copernicus, Newton and Einstein are among the most famous scientists but none of them were outstanding in terms of their laboratory experiments.
Darwin is not a famous scientist because of his experimental results on seed dispersal or worms or movement in plants.
Meyer reminds us that for the early days of science intelligent design was not a controversial or career breaking interest. A. N. Whitehead is quoted:
“There can be no living science unless there is a widespread conviction in the existence of an Order of Things, in particular, of an Order of Nature.”
This Whitehead argues was provided by the Christian belief in the rationality of God.
Steve Fuller has amplified Whitehead’s observation. Science began because theists believed that an intelligent God made the universe to be intelligible to human beings made in his image.
Why has intelligent design which was so important in the origin of science become so completely rejected from modern science?
Sunday, March 28, 2010
The experiment that launched evolution.
"Charles Darwin did little experimental science. He did make several descriptive studies of barnacles and worms and some experimental studies about how species spread through seed dispersal and other processes. Yet his masterpiece, On the Origin of Species by Means of Natural Selection, contains neither a single mathematical equation nor any report of original experimental research. Yet he formulated a great scientific theory."
Stephen Meyer - Signature in the Cell p139
Stephen Meyer - Signature in the Cell p139
The Axe-Meyer Axis.
This is an attempt to state more clearly what I tried to say before...
How is Axe's published work relevant to ID?
Past posts for reference:
I was thinking...
J.Mol.Biol- 2000 -301-585-595
Controversial paper
Appearance of design
Making a functional protein from scratch is difficult. This is relevant in two situations(a) In a prebiotic soup making a protein to help stabilise or increase the function of a precellular replicon.
(b) after the origin of life the development of a brand new structural or functional protein which enhances the reproductive capacity of the organism.
The following argument is my version of what Stephen Meyer says on p206 and following in Signature in the Cell.
Most functional proteins are over 150 amino acids long. The average is estimated at around 300 amino acids long. With 20 different amino acids a protein 150 amino acids long gives a very large number of possible sequences - 10195 (which is a pretty big number)
Firstly in a prebiotic soup with an abundance of amino acids there are a number of possible ways in which amino acids can link up- however to get a folding protein we need peptide bonds. The probability of forming a peptide link is about 1 in 2.
To get a 150 amino acid molecule with peptide bonds the whole way along will be a probability of 1 in 1045.
Secondly in a prebiotic soup there will be 2 optical isomers of each amino acid. All the functional proteins in nature use only L isomers.
To get a 150 amino acid molecule with only L isomers the probability is also 1 in 10 45.
Thirdly there are constraints in terms of the exact order of amino acids that will produce a protein that can fold into a globular shape with the possibility of having a function.
Fourthly there are constraints in terms of the exact order of amino acids that will produce a protein that has a function.
The fourth issue was investigated by Robert Sauer in the late 1980's at MIT. Cassette mutagenesis was used to examine the tolerance to sequence change at a number of locations in a variety of proteins.
The results showed that the probability of acheiving a functional sequence in several small proteins was very low. In other words there are very few different combinations of amino acids that allow the function to be maintained.
The chance of hitting on one of these by chance was about 1 in 1063.
Doug Axe was interested in Sauer's work and began to wonder if he had underestimated how much protein sequences can vary and still retain function.
He developed a more rigorous mechanism to test this. The results in a paper published in 2004 were particularly important. On the basis of these results Axe was able to demonstrate that the ratio of functional sequences to non functional sequences for the enzyme beta-lactamase was 1 functional sequence to every 1 x1077.
Axe's work also allowed him to calculate the probabilities of finding any functional sequence amongst the possible sequences. This was done by looking at the probability of sequences being able to form stable folds (a necessary pre-requisite for stable 3D structure)
On the basis of his work he calculated the ratio of sequences able to form stable 3D structures to those which were not able to as 1 to 10 74.
A comparison of these odds:
The odds of finding a 150 amino acid sequence able to fold into a stable 3D shape is equivalent to finding a single marked atom out of all the atoms in a a billion Milky Ways (that is the galaxy[this is the star system rather than the chocolate bar] rather than the chocolate bar)
These are unpromising odds to say the least.
For a functional protein in a prebiotic soup the odds are considerably worsened.
For a complex of functional proteins occuring at the same time the odds are also considerable worsened.
The odds of a 150 amino acid protein with stable 3D shape in a prebiotic soup is 1 in 10 to 164 this is well below the entire probabalistic resources of the entire history of the entire universe.
How is Axe's published work relevant to ID?
Past posts for reference:
I was thinking...
J.Mol.Biol- 2000 -301-585-595
Controversial paper
Appearance of design
Making a functional protein from scratch is difficult. This is relevant in two situations(a) In a prebiotic soup making a protein to help stabilise or increase the function of a precellular replicon.
(b) after the origin of life the development of a brand new structural or functional protein which enhances the reproductive capacity of the organism.
The following argument is my version of what Stephen Meyer says on p206 and following in Signature in the Cell.
Most functional proteins are over 150 amino acids long. The average is estimated at around 300 amino acids long. With 20 different amino acids a protein 150 amino acids long gives a very large number of possible sequences - 10195 (which is a pretty big number)
Firstly in a prebiotic soup with an abundance of amino acids there are a number of possible ways in which amino acids can link up- however to get a folding protein we need peptide bonds. The probability of forming a peptide link is about 1 in 2.
To get a 150 amino acid molecule with peptide bonds the whole way along will be a probability of 1 in 1045.
Secondly in a prebiotic soup there will be 2 optical isomers of each amino acid. All the functional proteins in nature use only L isomers.
To get a 150 amino acid molecule with only L isomers the probability is also 1 in 10 45.
Thirdly there are constraints in terms of the exact order of amino acids that will produce a protein that can fold into a globular shape with the possibility of having a function.
Fourthly there are constraints in terms of the exact order of amino acids that will produce a protein that has a function.
The fourth issue was investigated by Robert Sauer in the late 1980's at MIT. Cassette mutagenesis was used to examine the tolerance to sequence change at a number of locations in a variety of proteins.
The results showed that the probability of acheiving a functional sequence in several small proteins was very low. In other words there are very few different combinations of amino acids that allow the function to be maintained.
The chance of hitting on one of these by chance was about 1 in 1063.
Doug Axe was interested in Sauer's work and began to wonder if he had underestimated how much protein sequences can vary and still retain function.
He developed a more rigorous mechanism to test this. The results in a paper published in 2004 were particularly important. On the basis of these results Axe was able to demonstrate that the ratio of functional sequences to non functional sequences for the enzyme beta-lactamase was 1 functional sequence to every 1 x1077.
Axe's work also allowed him to calculate the probabilities of finding any functional sequence amongst the possible sequences. This was done by looking at the probability of sequences being able to form stable folds (a necessary pre-requisite for stable 3D structure)
On the basis of his work he calculated the ratio of sequences able to form stable 3D structures to those which were not able to as 1 to 10 74.
A comparison of these odds:
The odds of finding a 150 amino acid sequence able to fold into a stable 3D shape is equivalent to finding a single marked atom out of all the atoms in a a billion Milky Ways (that is the galaxy[this is the star system rather than the chocolate bar] rather than the chocolate bar)
These are unpromising odds to say the least.
For a functional protein in a prebiotic soup the odds are considerably worsened.
For a complex of functional proteins occuring at the same time the odds are also considerable worsened.
The odds of a 150 amino acid protein with stable 3D shape in a prebiotic soup is 1 in 10 to 164 this is well below the entire probabalistic resources of the entire history of the entire universe.
Thursday, March 18, 2010
The appearance of Design.
The universe itself and living organisms in particular have the appearance of being designed. Human intelligence from very early times has concluded from this appearance of design that there must be a designer.
Darwin’s theory was an alternative seeking to explain the appearance of design without an actual designer.
In terms of biology ID writers suggest three key areas for investigation that interest me.
1. The origin of life itself.
2. The origin of new functional proteins
3. The origin of interdependent proteins where multiple proteins are fine tuned for a particular function and all are required simultaneously for minimal function.
With regards to area 1 I am interested in working through Stephen Meyers recent book – Signature in the Cell.
With regards to area 2 the key research is the investigation of the relative quantities of functional to non-functional proteins amongst all possible proteins. How easy is it to produce an entirely new functional protein? I am not talking about variants within a protein family but the production of an entirely new structure with a new function with no amino acid sequence homology to any other functional protein.
One way to investigate this is to ask how easily protein structure and function degrades when you change one or more amino acids around the active site of an enzyme or elsewhere in its structure.
This gives an increasingly clear picture of the size of the islands of protein functionality in the vast ocean of possible protein amino acid sequences.
It is this kind of experiment that Doug Axe did at Cambridge.
Some previous posts on this:
How big is the hole?
I was thinking..
Axe's paper
Axe's paper
Which Golf Course?
Darwin’s theory was an alternative seeking to explain the appearance of design without an actual designer.
In terms of biology ID writers suggest three key areas for investigation that interest me.
1. The origin of life itself.
2. The origin of new functional proteins
3. The origin of interdependent proteins where multiple proteins are fine tuned for a particular function and all are required simultaneously for minimal function.
With regards to area 1 I am interested in working through Stephen Meyers recent book – Signature in the Cell.
With regards to area 2 the key research is the investigation of the relative quantities of functional to non-functional proteins amongst all possible proteins. How easy is it to produce an entirely new functional protein? I am not talking about variants within a protein family but the production of an entirely new structure with a new function with no amino acid sequence homology to any other functional protein.
One way to investigate this is to ask how easily protein structure and function degrades when you change one or more amino acids around the active site of an enzyme or elsewhere in its structure.
This gives an increasingly clear picture of the size of the islands of protein functionality in the vast ocean of possible protein amino acid sequences.
It is this kind of experiment that Doug Axe did at Cambridge.
Some previous posts on this:
How big is the hole?
I was thinking..
Axe's paper
Axe's paper
Which Golf Course?
Wednesday, February 24, 2010
JBS Haldane on the origin of Life
If the minimal organism involves not only the code for its proteins, but also twenty types of soluble RNA, one for each amino acid, and the equivalent of ribosomal RNA, our descendents may be able to make one, but we must give up the idea that such an organism could have been produced in the past, except by a similar pre-existing organism or by an agent, natural or supernatural, at least as intelligent as ourselves, and with a good deal more knowledge.
J. B. S. Haldane;
Data needed for a blueprint of the first organism, 1951.
Published posthumously in S. Fox (ed) The origins of prebiological systems and of their molecular matrices,
Proceedings of a conference at Wakulla Springs, Florida, 27-30 October 1963
Academic Press. New York 1965, p12.
Does anyone know anything about the context of this quote?
I have this page with some other quotes of JBS Haldane.
J. B. S. Haldane;
Data needed for a blueprint of the first organism, 1951.
Published posthumously in S. Fox (ed) The origins of prebiological systems and of their molecular matrices,
Proceedings of a conference at Wakulla Springs, Florida, 27-30 October 1963
Academic Press. New York 1965, p12.
Does anyone know anything about the context of this quote?
I have this page with some other quotes of JBS Haldane.
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