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Supercomputer Sets Protein-Folding Record
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."
..it's a rather poor article. It talks in very basic terms about proteins and their folding, talks a bit more about the scientist who founded the institute behind the computer, and says fuck-all about the construction of the computer itself.
Bah. For a publishing house of Nature Publishing Group's (intellectual and economic) muscle, one should expect more.
"The agriculture ministry is not in charge of Gundam" - Japanese ministry official.
The performance of a 512-node Anton machine is over 17,000 nanoseconds of simulated time per day for a protein-water system consisting of 23,558 atoms
So... how many libraries of congress per second??
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.
If Pandora's box is destined to be opened, *I* want to be the one to open it.
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.
46 & 2
That's a little unfair to Folding@Home. Shaw has a lot of resources to pour into this project - he's lured faculty members away from universities to work for him instead and has the equivalent of several large labs worth of advanced researchers. He also has an immensely larger budget than most non-profit labs, and he's self-employed so he doesn't have to answer to granting agencies or tenure committees. I think what he's doing is great but he's really one of the only people who could have pulled this off. It's difficult to know what approach will work best in advance, and both Shaw and Vijay Pande have been very innovative in approaching the problem from completely different angles.
By the way, this approach has been tried before with less stellar results - I'm thinking of the MD-GRAPE project in Japan. You're also assuming that every problem is equally well suited towards custom ASICs, but actually, molecular dynamics is far easier to do this with than many other methods. For instance, Rosetta (Rosetta@Home and Fold.It) is doing structure prediction, not folding, using a mostly statistics-based energy function and Monte Carlo sampling, and this isn't something you can trivially offload to a specialized chip. In that case, distributed computing is by far the most efficient solution.
No, Anton simulated one millisecond over the course of a hundred days. The previous recordholder took roughly the same time to do a hundredth of the work. (This was probably the RIKEN MDGRAPE-3, but again, documentation is le sparse.)
Bio questions? Ask me to start a Q&A journal. Computer analogies available for most topics!
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.
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.
"I'm too busy to research this and form an educated opinion, but I do have time to tell everyone my uninformed opinion."
It is complex, but you are ignoring the relative isolation between levels that exists in the human, and rat, body.
Protein folding may be complex, but most of it is irrelevant detail. What's usually important is the final shape that one ends up with, e.g. But when wants to modify that process, then the details of that process become important. This is roughly equivalent to...at the level that I work, I pay no attention to how the compiler is going to optimize my code. If I wanted to modify that I'd need to pay attention to things at a much finer level of detail.
It *is* true that people tend to oversimplify things they aren't dealing with directly. But to make it a fair statement it needs to be made fully *that* general. (This doesn't make you original assertion false, but observationally it *is* false. I've never known a knowledgeable geek that oversimplified the biochemistry of life in the way that you painted. I'm sure they exist, but they aren't, as you implied, common. If they are common among your friends, well, then you have some uncommon friends.)
I think we've pushed this "anyone can grow up to be president" thing too far.