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Biotech Supercomputing Science

Supercomputer Sets Protein-Folding Record 63

Nicros writes with this snippet from Nature News: "A specially designed supercomputer named Anton has simulated changes in a protein's three-dimensional structure over a period of a millisecond — a time-scale more than a hundred-fold greater than the previous record. ... The simulations revealed how the proteins changed as they folded, unfolded and folded again. 'The agreement with experimental data is amazing,' says Chandra Verma, a computational structural biologist at the Bioinformatics Institute of the Agency for Science, Technology and Research in Singapore. Simulating the basic pancreatic trypsin inhibitor over the course of a millisecond took Anton about 100 days — roughly as long as computers spent toiling over previous simulations that only spanned 10 microseconds."
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Supercomputer Sets Protein-Folding Record

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  • by Anonymous Coward on Sunday October 17, 2010 @05:40AM (#33922802)

    It's about someone (a rich someone) building a really big computer to tackle a really, really, really, really, really, really, really complex physical/chemical problem that we currently know dick all about.

    If protein folding was equivalent to fluency in English, we'd be at "bwawubda?"

  • by Anonymous Coward on Sunday October 17, 2010 @07:37AM (#33923118)

    over a period of a millisecond — a time-scale more than a hundred-fold greater than the previous record

    This phrasing always confuses me where they say "It's this much faster so it's x times greater!"

    So they're a hundred fold greater and they're a millisecond...? Does that mean the other guy took 1/100ths of a millisecond?

  • applause! (Score:3, Insightful)

    by StripedCow ( 776465 ) on Sunday October 17, 2010 @08:31AM (#33923266)

    This research is extremely important for finding new drugs, and therefore I applaud the originators of the project, especially D.E. Shaw who apparently put also a lot of funding into it. I wish more (rich) people put their money into such immensely useful projects. It is not just a noble thing to do, it is also smart, since we all could one day benefit from this kind of research.

  • by serviscope_minor ( 664417 ) on Sunday October 17, 2010 @08:47AM (#33923324) Journal's a rather poor article. It talks in very basic terms

    That's because it's in nature news, which does rather high-level, short coverage of a wide range of topics for a very broad scientific audience. It's meant to be a "hey look this is cool" article, that you can read up more about if you are interested and have the right kind of background. Perhaps you were thinking it was a ahort or regular article?

  • not really (Score:3, Insightful)

    by pigwiggle ( 882643 ) on Sunday October 17, 2010 @09:04AM (#33923400) Homepage

    This has been the promise of computer simulation - "in silico" drug design - for decades. It hasn't panned out. And I say this as someone who makes a living doing exactly what these folks have done. High throughput bench work is far more efficient, time and money wise, than computer simulation. Hard to say when or if that will change.

  • by the gnat ( 153162 ) on Sunday October 17, 2010 @10:26AM (#33923776)

    The best way is to just compare them to the actual structure which is known from x-ray crystallography and NMR studies.

    And so far, this is the only way that most researchers are willing to trust. There is a very good reason why these folding studies tend to focus on a small group of well-defined model systems, because the folded native structure is already very well understood, and it provides an essential constraint on the interpretation of results. Using ab initio physics calculations like this for truly blind structure prediction would be a complete waste of time, and the entire field figured this out decades ago.

  • Ah, the human body (Score:1, Insightful)

    by Anonymous Coward on Sunday October 17, 2010 @10:41AM (#33923840)

    I love it how simple-minded tech geeks, usually IT guys, programmers and even people who should know better like electrical engineers, think that the internet is more complex than the human body... Here we have ONE molecule, simulated for a lousy millisecond, and it took more than THREE MONTHS. How many molecules in the human body? Our body is performing a truly staggering amount of computation. Actually, every bit of matter is, everything including "inanimate" matter, it's really all the same. We just happen to be more complex.

    I wonder how accurate this is? Information Processing in Human Body [] And when we do start uderstanding how the huge amount of molecules in one cell behaves, we can maybe start understanding how the huge number of cells becomes US. Including things like diseases and aging. Once that is done, hello life-extension! Isn't that more interesting than tin cans floating in a vacuum? I think so. But then again, I'm crazy; I think wanting to have more time is the same as wanting to have more space. It's humans exploring the universe, it's just that we need to live longer than we do if we think we really are going to explore the universe. After all, can a mayfly explore a city? It'll be dead in three days. That's us, in space.

  • by the gnat ( 153162 ) on Sunday October 17, 2010 @11:29AM (#33924104)

    This was not an ab initio, calculation. It's all atom MD, which itself is an approximation

    Sorry, I meant "ab initio MD", although I realize that to a chemist or physicist this is a total oxymoron. (My background is molecular biology and bioinformatics, where we try not to think about quantum chemistry.) I should have written "physically-based", if you prefer, as opposed to the knowledge-based approaches that have been most successful for de novo structure prediction. (I think most MD "force fields" are ultimately based on genuinely ab initio QM calculations.)

  • by blackraven14250 ( 902843 ) on Sunday October 17, 2010 @12:06PM (#33924314)

    Good thing F@H runs on the GPU, which is many times faster than the CPU at these operations.

    Also, don't forget what it takes to build supercomputer capable of doing this, and that resources put into building supercomputers are then not available for the consumer market. Distributing this stuff allows for a compromise between absolute best performance and letting people have powerful computers at home.

  • Re:not really (Score:3, Insightful)

    by WrongMonkey ( 1027334 ) on Sunday October 17, 2010 @12:59PM (#33924620)
    I totally agree with you. I think it should always be pointed out the inherent limitation of these models. D.E. Shaw Research, Folding@home and many others use a force-field model that is fundamentally Newtonian. It doesn't take into account any quantum dynamics, it can't model the formation or dissociation of chemical bonds and most of the simulation parameters aren't much better than a wild guess. There used to be an implicit assumption in the computational chemistry community that all of those little errors would cancel out for large molecules, such as proteins. But, personally, I don't think that assumption has held up very well to experimental scrutiny.
  • by Anonymous Coward on Sunday October 17, 2010 @01:18PM (#33924770)
    The physicists have been doing protein folding for decades now. We know the basics of the physics but it requires a lot of computer power to perform useful simulations. This article is probably just another small step along the way. But if they cannot explain exactly what they have done that is new, then they probably haven't done so much that is new.
  • by SoftwareArtist ( 1472499 ) on Sunday October 17, 2010 @01:33PM (#33924880)

    Actually, Folding@Home can also simulate these time scales by means of Markov state models. The trajectory is pieced together out of data collected from many short simulations, whereas the Anton trajectory is generated from a single MD run, but in practice that distinction is usually irrelevant. Protein dynamics are stochastic, so for any time scale longer than about 1 ns, both approaches given equally "realistic" or "valid" trajectories.

    That's not to criticize Anton. It's an amazing piece of hardware and they're doing amazing work with it. But of the two approaches, Markov state models are probably going to prove more valuable in the end. They make more efficient use of whatever computational resources you have available, they give more insight into the structure of the folding pathway, and they can be run on commodity hardware that many more people have access to. David Shaw has even admitted they'll eventually have to start using them. By the third generation of Anton, he expects to have hit limits on how far they can parallelize a single MD run, so Markov state models will be the only way they can keep adding processing power.

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