Dr Baker gave out some science news here. Science News
It took a bit of poking and proding, but we got some cool news. Enjoy! :thumbsup::beer:
It took a bit of poking and proding, but we got some cool news. Enjoy! :thumbsup::beer:
Many of you have suggested that I give more frequent feedback on what is happening with Rosetta@home. I'm very happy to do this, and
will try to make nightly posts here (I don't promise every day!). I'll also start a second thread where people can post comments/questions related to the journal which I can try to answer as well.
It has been an extremely exciting week for the project! Divya and I for the past two months have been improving the algorithms in rosetta based on tests on a set of ten proteins whose names you are probably quite familiar with by now. David Kim tested the improved method on an additional set of about 25 proteins. He has been so busy trying to fix the problems causing the WU errors that he hasn't had much time to analyze the results, but David and I took a quick look yesterday and the results are pretty amazing--for about half of them the lowest energy structure was quite close to the correct (native) structure. Since we hadn't used this set in improving the method, it suggests that the improvements we have made are pretty general, and that we are making significant progress towards solving the protein structure prediciton for small proteins.
It is hard to describe how electrifying (and almost scary!) this is. the protein structure prediction problem is perhaps the longest standing problem in molecular biology. it has been known for forty years that the structures of proteins are determined by their amino acid sequences, but as recently as five or six years ago it was generally thought that the prediction problem was completely intractable as very little progress had been made. starting about this time we showed in the CASP blind tests that with the rosetta low resolution structure prediction method rough models could be built for small proteins that in some cases were reasonably similar in topology to the true structure, but the predicted structures were never accurate at the atomic level. we have worked for the past five years on developing high resolution refinement methods that could take these rough models and refine them to much higher accuracy. this goal remained elusive for the first few years, but about a year and a half ago we made a breakthrough and found that we could make very accurate predictions for some proteins using a trick that involves folding not only the sequence of the protein of interest but also the sequences of a large number of evolutionarily related homologs. using this method we made the first high accuracy ab initio structure prediction in CASP (the last target in CASP6) and did further tests which showed accurate predictions for 6 of 16 proteins which were published in Science last year (I think there is a link to the paper on the home page).
however, this work did not achieve the goal of predicting structure accurately from the amino acid sequence of a protein alone as we had to resort to evolutionary information. achieving this goal has been the central aim of rosetta@home thus far, and as I said above it is almost a "holy grail" of computational biology. so now, looking at David Kim's results and seeing that for quite a few proteins we are coming close to predicting structure from their amino acid sequences without any other information is pretty breathtaking.
Divya is now preparing figures to post on the science page which show the results on the 10 protein set we have been working on, and David will post results on his larger set once he can finish the analysis after he has implemented his clever fix to the unhandled exception errors.
it is clear for the still large number of proteins for which we are failing that the problem is not enough sampling, even with 100,000 independent folding runs we are not coming close enough to the native strucutre to land in its energy minimum. so we need more cpu power! it is kind of amazing that solving such a long standing scientific problem depends so crucially on the efforts of volunteers like yourselves! I don't know how much more cpu power it will take, but if you can each recruit ten friends or relations ...
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