From: Eric A Brenner (ericbrenner_at_utexas.edu)
Date: Sat Dec 17 2016 - 19:02:39 CST
Thanks for the info! Is there any other software you'd recommend I use for
these purposes? Also, I was using the 36m parameters, but I could
definitely stand to learn more about it.
On Dec 17, 2016 6:48 PM, "JC Gumbart" <gumbart_at_physics.gatech.edu> wrote:
Completely unfeasible. Based on our benchmark for a 15k-atom system on
807 runs * 6000 ns * 29 SUs/ns = 140 million SUs.
Protein folding times are sequence dependent AND force-field dependent (as
are the sampled structures!). In particular, force fields are generally
designed to reproduce properties of folded proteins*, meaning there are
even fewer guarantees they will work for random synthetic peptides (yet
another caveat - there’s no guarantee they would behave the same in
implicit solvent). I would suggest reading some of the protein folding
literature as a starting point.
*There is some work to move towards better representation of disordered
proteins; see, for example, http://www.nature.com/nmeth/journal/vaop/
On Dec 17, 2016, at 1:35 PM, Eric A Brenner <ericbrenner_at_utexas.edu> wrote:
I have 870 small peptides (10-20aa each) for which I'm trying to get
predicted structures. The reason I'm using NAMD and not something like
Rosetta is because the length of these peptides and the fact that they have
mimimal homology to any peptides in nature (since their sequences were
randomly generated, and then they were ran through a screen) causes
problems with the structure prediction programs I've tried. I decided to
run PSIPRED to get predicted secondary structures, put each peptide in said
secondary structure, and then run them through NAMD to see if the
secondary structures come apart and/or if supersecondary structures form.
I'm going to do the initial minimization in explicit solvent, but then
since explicit solvent calculations are slower (is that true? I've also
heard the opposite), I'm going to then switch to GBIS thereafter. I read
that supersecondary structures can take up to 6 microseconds to form. Is
running 870 peptides for 6 us feasible? Based on some preliminary runs, it
seems like it'll require a ton of computational power and a ton of time.
Granted, these tests were on CPU cores not GPU cores. I'm using the TACC
Lonestar5 supercomputer by the way (https://portal.tacc.utexas.
edu/user-guides/lonestar5). Anyways, do my ambitions seem reasonable or
should I rethink some of the technical aspects (e.g. running for way less
than 6 us instead)?
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