From: JC Gumbart (gumbart_at_physics.gatech.edu)
Date: Sat Dec 17 2016 - 18:48:50 CST
Completely unfeasible. Based on our benchmark for a 15k-atom system on Stampede,
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/ncurrent/full/nmeth.4067.html <http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.4067.html>
> 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 <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)?
> Thanks! :)
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