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This is the place where we will describe some of the outcomes and results of your folding work, provide a glimpse of future challenges and developments, and in general give you a better sense of where we are and where foldit hopes to go in the future.

Foldit scripting preview

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We've started working on adding Lua scripting, and here's a very rough preview of what it looks like now. This is just in a command line window, but there will also be support for scripts in the cookbook.

What do you think? What kind of API would you like to see? Let us know in the comments!

( Posted by  Seth Cooper 78 1834  |  Fri, 08/21/2009 - 21:04  |  10 comments )
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Poll: Outlines

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We recently added an option to turn the outlines on the protein structure on and off. This was initially for performance reasons, but it has also come up that the protein may look better without them as well. So, here's a poll to decide what we should do with the outlines, let us know what you think!

( Posted by  Seth Cooper 78 1834  |  Fri, 08/21/2009 - 19:07  |  1 comment )
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Design of inhibitors update

The results from the inhibitor design puzzle have come in and it appears that many of the players fully identified all of the hot-spot residues - those are the residues on the inhibitor that are crucial to inhibition in the natural inhibitor. This is very impressive because getting these hot-spot residues correctly requires a combination of tools that Rosetta provides, including sidechain redesign and minimization.

We will next provide several other puzzles similar to this one, where we know what the hot-spot residue identities are, but we shaved those off and you can try to recapitulate them. The first in this set of puzzles is the structure of human growth hormone bound to its receptor.

Following a few of these puzzles we would like to ask for your help in improving our designs for a variety of protein targets. I'm looking forward to your participation and am eager to see what design possibilities you could uncover that we miss.

( Posted by  sarelf 78 2765  |  Tue, 08/04/2009 - 23:30  |  0 comments )
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Mini CASP-like competition starts today

We have exciting news!
We were able to obtain sequences for proteins that are currently
unsolved, but will be released to the Protein Data Bank very soon!

In fact, today's first puzzle will be released to the PDB next week,
so we need you to start folding quickly!

After the first puzzle (released today) expires on August 8th, we will
release another puzzle where you will have more time. The second
protein will not be deposited into the PDB until the end of the month.

We will give you starting models outputted from Rosetta@home, and
since we have no idea which predictions are correct we will try to
give you as diverse a set as possible.

We are very excited to be able to run this blind experiment where the
proteins will be released so soon!
This will be perfect practice for everyone as CASP9 starts next May,
and it will help us figure out what are the best Rosetta models to use
as starting points for Foldit.

( Posted by  David Baker 78 2765  |  Mon, 08/03/2009 - 23:12  |  0 comments )
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The key secret to finding best structures: Exploration

This is story about the Puzzle 138 (Rosetta Decoy 2). It is fascinating because it uncovers where we as developers should be focusing our design energy, and it also indicates that a change of game playing strategy may benefit all results. The short story is pay close attention to solutions that have relatively good score (but perhaps not the best), but appear noticeably different in structure from other solutions.

To demonstrate the point here is the plot of the initial solutions of puzzle 138. Vertical axis is the foldit score (expressed as a rosetta energy function where lower is better). The horizontal axis is the root mean square distance of backbone molecules, so the smaller it is the closer we are to the solution in the sense of per-molecule distance. The blue dot is the native structure from x-ray crystallography, so it could still have some slight errors, but it's the closest we know ho to get to the real thing. The graph shows that there is a large groups of solutions that are slight modifications of the starting solution, that is the molecules don't really move a lot. Still we see that to get to the native, lots of molecule movement needs to happen (towards the left on the graph). In fact we see that foldit solutions are hitting a virtual wall, where the score function lowers without approaching the solution. You will also notice that a lone exploerer has a solution that according to the foldit score is not the best, but on the graph appears much closer to the solution.
Solution of Puzzle 138Solution of Puzzle 138

The question in our mind was this: if we started from this lone island discovered by foldit players, could the players do much better? So we posed another puzzle with the starting point shown in the black in the second image. The answer is emphatically yes! The Cyan points on the graph show the solutions after the second puzzle, which effectively shows that the solution is found.

This finding hold a key to all successful strategies. It's good to explore, and to actually move the protein in significant ways. you may get more points with hard-to-notice shakes and wiggles, but to truly explore better solutions one must venture into the unknown. It also shows that although the solution may not be good right away, after a bit more game play the significantly better solution may be found. So, exploration is the key.

In the near future we will focus on ways to encourage exploration within the game play. For the foldit players I would suggest paying close attention to the solutions that appear relatively close and likely worse in score to the best known solution, but that are significantly different in shape. Every time one of these solutions is found, it should be carefully explored. Chances are the true native solution may be nearby.

( Posted by  zoran 78 2765  |  Thu, 07/16/2009 - 19:21  |  5 comments )
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Developed by: UW Center for Game Science, UW Institute for Protein Design, Northeastern University, Vanderbilt University Meiler Lab, UC Davis
Supported by: DARPA, NSF, NIH, HHMI, Microsoft, Adobe, RosettaCommons