By Wand Agency
Classical and Quantum Information in DNA (Google Workshop on Quantum Biology)
The lecturer (Gretchen) shows that quantum information is ‘sandwiched’ along the whole of the DNA molecule, as well as hypothesizing that quantum information must somehow be involved in protein folding to explain the ‘increase of information’ as the linear information from the DNA becomes linear plus ’3-Dimensional’ information in the final folded state of the protein. She also proposed a test and said that if proteins folded differently (or more likely the protein will not fold at all) from the same linear information when the quantum information is disturbed/destroyed that this would be a very strong indication that quantum information was also essential in protein folding, besides the linear information from DNA being essential for protein folding.
Of related note:
The ‘Fourth Dimension’ Of Living Systems
The relevance of continuous variable entanglement in DNA – June 21, 2010
Abstract: We consider a chain of harmonic oscillators with dipole-dipole interaction between nearest neighbours resulting in a van der Waals type bonding. The binding energies between entangled and classically correlated states are compared. We apply our model to DNA. By comparing our model with numerical simulations we conclude that entanglement may play a crucial role in explaining the stability of the DNA double helix.
Quantum entanglement holds together life’s blueprint
Excerpt: “If you didn’t have entanglement, then DNA would have a simple flat structure, and you would never get the twist that seems to be important to the functioning of DNA,” says team member Vlatko Vedral of the University of Oxford.
Quantum Computing in DNA - Hameroff
Excerpt: Hypothesis: DNA utilizes quantum information and quantum computation for various functions. Superpositions of dipole states of base pairs consisting of purine (A,G) and pyrimidine (C,T) ring structures play the role of qubits, and quantum communication (coherence, entanglement, non-locality) occur in the “pi stack” region of the DNA molecule.,,, We can then consider DNA as a chain of qubits (with helical twist).
Output of quantum computation would be manifest as the net electron interference pattern in the quantum state of the pi stack, regulating gene expression and other functions locally and nonlocally by radiation or entanglement.
of related note;
Stephen Meyer - The Rarity Of Functional Proteins; The Epigentic Information For Body Plans - video
Estimating the prevalence of protein sequences adopting functional enzyme folds: Doug Axe:
Excerpt: Starting with a weakly functional sequence carrying this signature, clusters of ten side-chains within the fold are replaced randomly, within the boundaries of the signature, and tested for function. The prevalence of low-level function in four such experiments indicates that roughly one in 10^64 signature-consistent sequences forms a working domain. Combined with the estimated prevalence of plausible hydropathic patterns (for any fold) and of relevant folds for particular functions, this implies the overall prevalence of sequences performing a specific function by any domain-sized fold may be as low as 1 in 10^77, adding to the body of evidence that functional folds require highly extraordinary sequences.
Let’s look at the complexity which goes into crafting the shape of just one single protein molecule. Complexity, instead of rarity, will give us a better indication if a protein molecule is indeed the handi-work of an infinitely powerful Creator.
In the year 2000 IBM announced the development of a new super-computer, called Blue Gene, which was 500 times faster than any supercomputer built up until that time. It took 4-5 years to build. Blue Gene stands about six feet high, and occupies a floor space of 40 feet by 40 feet. It cost $100 million to build. It was built specifically to better enable computer simulations of molecular biology. The computer performs one quadrillion (one million billion) computations per second. Despite its speed, it was estimated to take one entire year for it to analyze the mechanism by which JUST ONE “simple” protein will fold onto itself from its one-dimensional starting point to its final three-dimensional shape.
"Blue Gene's final product, due in four or five years, will be able to "fold" a protein made of 300 amino acids, but that job will take an entire year of full-time computing." Paul Horn, senior vice president of IBM research, September 21, 2000
Networking a few hundred thousand computers together has reduced the time to a few weeks for simulating the folding of a single protein molecule:
A Few Hundred Thousand Computers vs. A Single Protein Molecule - video
As well, despite some very optimistic claims, it seems future 'quantum computers' will not fair much better in finding functional proteins in sequence space than even a idealized 'material' supercomputer of today can do:
The Limits of Quantum Computers – March 2008
Excerpt: "Quantum computers would be exceptionally fast at a few specific tasks, but it appears that for most problems they would outclass today’s computers only modestly. This realization may lead to a new fundamental physical principle"
The Limits of Quantum Computers - Scott Aaronson - 2007
Excerpt: In the popular imagination, quantum computers would be almost magical devices, able to “solve impossible problems in an instant” by trying exponentially many solutions in parallel. In this talk, I’ll describe four results in quantum computing theory that directly challenge this view.,,, Second I’ll show that in the “black box” or “oracle” model that we know how to analyze, quantum computers could not solve NP-complete problems in polynomial time, even with the help of nonuniform “quantum advice states”,,,
Here is Scott Aaronson's blog in which refutes recent claims that P=NP (Of note: if P were found to equal NP, then a million dollar prize would be awarded to the mathematician who provided the proof that NP problems could be solved in polynomial time):
Excerpt: Quantum computers are not known to be able to solve NP-complete problems in polynomial time.
Protein folding is found to be a 'intractable NP-complete problem' by several different methods. Thus protein folding will not be able to take advantage of any advances in speed that quantum computation may offer to any other problems of computation that may be solved in polynomial time:
Combinatorial Algorithms for Protein Folding in Lattice
Models: A Survey of Mathematical Results – 2009
Excerpt: Protein Folding: Computational Complexity
NP-completeness: from 10^300 to 2 Amino Acid Types
NP-completeness: Protein Folding in Ad-Hoc Models
NP-completeness: Protein Folding in the HP-Model
Another factor severely complicating man's ability to properly mimic protein folding is that, much contrary to evolutionary thought, many proteins fold differently in different 'molecular' situations:
The Gene Myth, Part II - August 2010
Excerpt: the rate at which a protein is synthesized, which depends on factors internal and external to the cell, affects the order in which its different portions fold. So even with the same sequence a given protein can have different shapes and functions. Furthermore, many proteins have no intrinsic shape, taking on different roles in different molecular contexts. So even though genes specify protein sequences they have only a tenuous influence over their functions.
As a sidelight to the complexity found for folding any relatively short amino acid sequence into a 3-D protein, the complexity of computing the actions of even a simple atom, in detail, quickly exceeds the capacity of our most advanced supercomputers of today:
Delayed time zero in photoemission: New record in time measurement accuracy - June 2010
Excerpt: Although they could confirm the effect qualitatively using complicated computations, they came up with a time offset of only five attoseconds. The cause of this discrepancy may lie in the complexity of the neon atom, which consists, in addition to the nucleus, of ten electrons. "The computational effort required to model such a many-electron system exceeds the computational capacity of today's supercomputers," explains Yakovlev.
Also of interest to the extreme difficultly man has in computing the folding of a single protein within any reasonable amount of time, it seems water itself, (H2O), was 'designed' with protein folding in mind:
Protein Folding: One Picture Per Millisecond Illuminates The Process - 2008
Excerpt: The RUB-chemists initiated the folding process and then monitored the course of events. It turned out that within less than ten milliseconds, the motions of the water network were altered as well as the protein itself being restructured. “These two processes practically take place simultaneously“, Prof. Havenith-Newen states, “they are strongly correlated.“ These observations support the yet controversial suggestion that water plays a fundamental role in protein folding, and thus in protein function, and does not stay passive.
Water Is 'Designer Fluid' That Helps Proteins Change Shape - 2008
Excerpt: "When bound to proteins, water molecules participate in a carefully choreographed ballet that permits the proteins to fold into their functional, native states. This delicate dance is essential to life."