From: Dr. Eddie (eackad_at_gmail.com)
Date: Thu Jul 26 2012 - 16:40:05 CDT
Thanks Aron. I guess there is no way to make a small perturbation the an
already equilibrated protein. I want to have good statistics for distance
distributions in the equilibrated protein so having multiple runs helps.
But I guess changing the seed can just thrust me back into a parameter
space where it will likely take just as long to re-reach equilibrium. Right?
I have compared my rmsd to the initial frame as well since it seems to be a
standard approach and does make sense, but I am also curious if others have
a different method. My understanding was this is done because once the rmsd
has leveled off your results are converged. I have noticed that sensitive
things like the distance distribution between two residue alpha-carbons
becomes very narrow once the rmsd of the protein has equilibrated. Prior to
equilibration I get broader and multipeaked distributions.
Thanks,
Eddie
On Thu, Jul 26, 2012 at 4:07 PM, Aron Broom <broomsday_at_gmail.com> wrote:
> I'm not sure if that would show you what you want. If your run has
> stabilized, it suggests you are now in some kind of reasonably deep
> minimum. Presumably you are thinking of doing multiple runs to make sure
> that it is actually the deepest minimum near to your starting point, and if
> so, randomizing the seed from your already equilibrated structure may end
> up just telling you that you have high walls around that minimum, even if
> there are other deeper minima nearby.
>
> Also, in terms of using the RMSD a measure of the simulation stabilizing,
> do you just plot the RMSD as compared to the first frame? That is
> generally what I've done, but I wonder if others have different
> approaches? The big problem with that is the ambiguity of the RMSD, that
> is, if the RMSD levels off at 3A, it means that two structures in the last
> part of your simulation are different from the starting structure by 3A,
> but they could be more different than that from one another. I've tried
> using VMD to do an RMSD versus lag time or something, which would be a kind
> of fluctuation measure, and found that could be more sensitive. I'd like
> to know what others do with this, maybe there is something obvious I've
> missed?
>
> ~Aron
>
>
> On Thu, Jul 26, 2012 at 4:55 PM, Dr. Eddie <eackad_at_gmail.com> wrote:
>
>> Hi all,
>> I've been simulating a protein with NAMD using constant pressure
>> and temperature and PME. It takes anywhere from 10-24 ns for the rmsd of
>> the protein's backbone to level-off. I'd like to have multiple runs to
>> ensure good statistics but that overhead is debilitating. Would I be able
>> to simply continue a run that has stabilized (after, say 30 ns) using
>> different random seeds to get the same result as having multiple runs start
>> with different random seeds and each running for 30+ ns?
>> Has anyone tried this? I'd be interested in success or failure since my
>> time scales are too long to try it myself.
>> Thanks,
>> Eddie
>>
>>
>
>
> --
> Aron Broom M.Sc
> PhD Student
> Department of Chemistry
> University of Waterloo
>
>
-- Eddie
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