[gmx-users] Re: REMD analysis

[bharat gupta]

Dear Sir,

My main objective of carrying out REMD is to study peptide folding and if
possible to get some insight in protein design and folding. I read some
articles related to my work and they always show temp (replica_index)
graphs for 2-3 replicas , saying that the sufficient sampling had been
achieved. In my case I checked the replica_temp for first three replicas (
https://www.dropbox.com/s/gkbu0g0e1r37l57/replica_temp0.png) (
https://www.dropbox.com/s/sffq8rwghjublu0/replica_temp1.png)
 https://www.dropbox.com/s/ulccw8xabj66ktm/replica_temp2.png)

Almost all the three graphs are similar and the last 15ns shows that there
is no enough exchange (if I have analyzed correctly) ?? In this case the
acceptance ratio was fine and PE overlap was also good, but problem lies
with efficient sampling ?? What shall I do in such a case ??

On Sat, May 18, 2013 at 12:27 AM, Mark Abraham <mark.j.abraham at gmail.com>wrote:

> On Fri, May 17, 2013 at 4:26 PM, bharat gupta <bharat.85.monu at gmail.com
> >wrote:
>
> > Dear Sir,
> >
> > The the default bin width is 0.1 which I used for plotting the graphs.
> >
>
> That's nice. You need to decide what you need to do about it if you want
> graphs that look like those you see reported :-)
>
>
> > Another question is about your last reply to my thread "exchange
> acceptance
> > is a poor proxy for sampling efficiency". Sorry to ask this, but how to
> > check whether the sampling efficiency is optimal or not (what should be
> > optimal sampling efficiency) ??
> >
>
> Ah, now here's the real question :-) Spacing the replicas for optimal
> *flow* is a difficult problem, even for toy peptides, see e.g. papers by
> Nadler and Hansmann. Merely accepting exchanges does not imply flow. The
> belief is that getting flow enhances sampling, but the latter is hard to
> demonstrate without showing that "simulation time to converged sampling"
> actually reduces. I'm not aware of anybody who's actually done that - but
> it would certainly be an advantage if your application is interested in
> data at a range of temperatures.
>
> Mark
>
> On Fri, May 17, 2013 at 11:10 PM, Mark Abraham <mark.j.abraham at gmail.com
> > >wrote:
> >
> > > Histograms 101: The smaller your bin width, the more variations you
> see.
> > > The more samples you have, the fewer variations you see. A histogram
> that
> > > does not mention either of this is a work of fiction.
> > >
> > > The number of degrees of freedom in the potential energy distribution
> is
> > > also a factor in whether the distribution will look smooth for a given
> > bin
> > > width and number of samples.
> > >
> > > Mark
> > >
> > > On Fri, May 17, 2013 at 3:51 PM, bharat gupta <
> bharat.85.monu at gmail.com
> > > >wrote:
> > >
> > > > Dear Sir,
> > > >
> > > > I tried plotting the PE overlap using the following way :-
> > > >
> > > > 1. extract PE of each replica using g_energy
> > > > 2. get the PE distribution using g_analyze -f potential_0.xvg -dist
> > > > pot0.xvg
> > > > 3. used xmgrace to plot all the PE distribution graphs together.
> > > >
> > > > The same thing I did for temperature distribution for each replica.
> > > >
> > > > Here's the file for both PE overlap (
> > > > https://www.dropbox.com/s/895f1bi0hkuy884/pe_dist.png)
> > > > temp distribution (
> > > https://www.dropbox.com/s/ed66uop16blgqwa/temp_dist.png
> > > > )
> > > > Is this the correct way ??
> > > >
> > > >
> > > > But the plot doesnot look like this (
> > > > https://www.dropbox.com/s/fsuabkl7zrydnib/sample%20PE%20overlap.jpg
> ).
> > > Do i
> > > > have to normalize the data and then plot in order to get a smooth
> plot
> > > like
> > > > this one??
> > > >
> > > > --------
> > > > Bharat
> > > > --
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