There’s a brief squib in the AIP Physics News Updates today about new work on protein folding. “Protein folding” is a simple-sounding term for a really difficult problem: protein molecules are made up of chains of amino acids, which can be bent into a huge number of different possible configurations. In nature, though, these proteins are normally found in only one configuration. Correctly predicting the folded configuration of a given protein is an extremely difficult computational problem.
The paper highlighted by the AIP takes a new approach to the problem, employing some calculational tricks lifted from General Relativity:
Lapo Casetti (casetti@fi.infn.it) and Lorenzo Mazzoni have attempted to make the “energy landscape” method even more geometrical by characterizing the folding forces at work as being a form of curvature in the bowl-like well in which the protein is operating. This is analogous to what Albert Einstein did in characterizing gravity as the curvature of spacetime in which planets and stars move about. Mazzoni and Casetti seek to determine what it is about the curvature of the energy landscape that encourages proteins to fold and other polymers not to fold.
If ever there was a calculational technique to make me run shrieking in horror, this would have to be it…
My only real exposure to GR was a thoroughly bewildering crash course in tensor calculus as part of a “Cosmology for Idiots” class my junior year in college. Fifteen years later, I still have to suppress a shudder when I hear the words “Cristoffel Symbol.”
And protein folding was the topic of the single most annoying talk I’ve ever sat through, back in graduate school. It was part of a mandatory seminar series, and the speaker spent the better part of forty-five minutes talking in soul-crushing detail about the approximations they made, and the computational techniques they used, before ending with five minutes of material that can be summarized as “We find this one configuration, and when we check it against X-Ray crystallography, the actual configuration is something else. We’re not even close, and have no idea why. Thanks for listening, I’ll take questions now.”
That was ten years ago, and I’d still like to bash that guy in the head with a chair for wasting an hour of my life.
So the thought of applying general relativity to protein folding…. Well, let’s just say that it makes me glad to be an experimentalist.
Of course, the next question is how long it will take before some calculational technique from string theory gets applied to these calculations, and we’re treated to lots of preprints with titles like “AdS/CFT and β-amyloid”? Because, you know, that would just make my day…
Let me direct your attention to “The Isis Thesis” by Judy Kay King. Quoting from page 4:
“… path to the stars is referred to as Lambda-Genesis. Egyptian science not only supports that information can escape from the protein folding funnel landscape of a black hole, but it also reinforces String Theory concepts such as T-Duality and super- symmetry…”
or again page 334
“… All in all, the Egyptian model seems reasonable and supports tenets of String Theory and black hole theory, including Hawking Radiation. The macro-level earth spin system represents a quantum cell, where proteins fold to their native conformation in a folding funnel landscape with Kerr black hole dynamics. …”
I’m rather pleased that my brain can’t parse those sentences in any meaningful fashion.
Ow.
You bastard.
The phrase “protein folding funnel lanscape of a black hole” is particularly high-grade kookery. I’m amazed they didn’t manage to work a “nano” in there somewhere…
How does nature do it? Proteins do not start as straight strings in vacuum then diddled to equilibrium conformation. Protein is sequentially synthesized in a ribosome and linearly extruded into the intracellular medium in which it progressively reconfigures.
Protein folding calculation is not a nasty global optimization calculation. It is entirely local starting at one end with solvent and solutes interactions. The problem starts small and grows at worst as surface area as more of the protein molecule is extruded. That is not elegant, but it is useful.
I recommend going here:
folding_talk
and viewing the slides from a talk titled “Protein Structure Prediction: 25 years of disaster”.
From the look of the slides the actual talk must have been entertaining.
“Of course, the next question is how long it will take before some calculational technique from string theory gets applied to these calculations …”
How about RNA folding from large-N matrix field theory?
I roomed in Orsay, France with some British protein-folders for a couple of months in 1987. I was there to generate tables for the Handbook of Infrared Standards, they were there to use a new supercomputer the French had acquired.
They had to “vectorize” their code to take full advantage of the supercomputer’s architecture. This mostly involved removing the optimizations they had so laboriously incorporated over the years. When they were done, they ran the code on their old machine to confirm that it still gave the same results. It did. It also ran significantly faster.
You have to have a high tolerance for disappointment to work in that field.
Mine too. I think I’ll give it a whirl. . . .
Maybe the question is how to understand the states that proteins really are occupying and how these states really interact with each other. Can this be achieved in sufficient detail without string theory and the like I presume that people will be very happy. But if not? Who will be happy and who will be unhappy?
Well, string theory is already applied.. 🙂
http://arxiv.org/abs/hep-th/0104010