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.abra...@gmail.com>wrote: > On Fri, May 17, 2013 at 4:26 PM, bharat gupta <bharat.85.m...@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.abra...@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.m...@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 > > > > -- > > > > gmx-users mailing list gmx-users@gromacs.org > > > > http://lists.gromacs.org/mailman/listinfo/gmx-users > > > > * Please search the archive at > > > > http://www.gromacs.org/Support/Mailing_Lists/Search before posting! > > > > * Please don't post (un)subscribe requests to the list. 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