New results from Folding@home: paper #53

We have another new paper to come out in the Journal of Molecular Biology (paper #53 on our results web page).  This paper is on protein folding and is Dan Ensign’s first paper as lead author.  It’s also one of the first key results from the SMP client (I’m sure people feel like the SMP client has been out for quite a while, but this was actually a pretty fast turnaround, as analyzing the data, writing the paper, getting past peer review, and then getting published can easily take 12-24 months).

Dan wrote a nice non-technical summary of the paper which I’ll include here:

This paper describes the first set of results
generated using the SMP clients. The main advantage of using SMP for
these sorts of calculations is that the amount of computation that one
client can do is several times larger than the traditional clients.
This means that our simulations can get many times longer that before;
in fact, this has allowed us to generate several hundred folding
trajectories of the fastest-folding protein known, the HP35NleNle
variant of the villin headpiece subdomain. In this paper, because our
simulation time scales compare well to the 700-nanosecond experimental
folding time of this protein, AND we’ve generated enough trajectories
to get good statistics, we can shed some light on the experimental
results. To summarize the result, the first helix of the protein was
thought to be highly structured in the unfolded state of the protein;
we’ve suggested that structure in this part of the molecule is not
enough to lead to fast folding, and that longer time scales than the
700-ns mark may be present in this system.

Check out the movie: it shows some simulation we did
for this work, although watching one trajectory is emphatically NOT
statistically significant, which is the whole point of the paper!  The movie is from a interview I did and the main part I want to draw people’s attention to is the movie of the protein folding simulation — that simulation was from the SMP client and from the data set discussed in this paper.