[gmx-users] Re: gmx-users Digest, Vol 106, Issue 52

[vivek modi]

> Message: 2
> Date: Sat, 9 Feb 2013 23:36:20 +0530
> From: bipin singh <bipinelmat at gmail.com>
> Subject: Re: [gmx-users] Reference structure for PCA.
> To: Discussion list for GROMACS users <gmx-users at gromacs.org>
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> CAKb2Z-FU2qepKhOHfJE5RJ7Sk80DU8cSSzuQQCn-jgdpvbvpnQ at mail.gmail.com>
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>
> Hi vivek,
>
> I have few questions related to your query:
>
> During covariance matrix calculation, g_covar by default takes average
> structure of the trajectory as a reference structure then why you are
> giving it average structure of your trajectory (0-100ns) manually.
> Moreover without looking at your commands which you have used, it would be
> difficult for anyone that why are you getting these surprising results.
>

Thank you Bipin for your reply.
I am doing this because I have found that the result of the analysis
changes with the reference structure. And if my understating is correct
then g_covar by default does not take the complete trajectory structure as
the reference; it takes the average structure of the time window on which
we perform the analysis. Following are the commands which I am using for
g_covar:

1. g_covar  -f  *.xtc  -s  average0-100ns.pdb  -o  -v   -n  -b  70000  -e
 100000  -av  xyz.pdb  -l  xyz.log  -ascii  xyz.dat  -xpm  xyz.xpm  -mwa
 -ref (trajectory average is the reference)

2. g_covar  -f  *.xtc  -s  average70-100ns.pdb  -o  -v   -n  -b  70000  -e
 100000  -av  xyz.pdb  -l  xyz.log  -ascii  xyz.dat  -xpm  xyz.xpm  -mwa
 -ref
(70-100ns average is the reference)

Method 1 gives me low cosines (<.1).
Method 2 gives high cosines (~.5-.6) which I can not understand why. Also
the RMSF which these methods report are different.
Which reference structure is then appropriate and why ?


Thanks and Regards,

-Vivek.


On Thu, Feb 7, 2013 at 1:26 PM, vivek modi <modi.vivek2009 at gmail.com> wrote:
>
> > Hello,
> >
> > I have troubled you with a similar question before also, but I guess I
> need
> > some more clarification. My question is about the reference structure in
> > PCA analysis.
> > I have 100ns long protein simulation which I want to analyze using PCA.
> The
> > RMSD shows fluctuations upto initial 25-30ns and then becomes very
> stable.
> > I have performed PCA on the last 30ns window of the simulation where I
> > assume the simulation has converged (I also did on other time windows as
> > well).
> >
> > The question is this:
> > I did the analysis on the last 30ns window in two ways by taking two
> > different reference structures.
> >
> > a. I take the average structure of the trajectory (0-100ns) as
> > the reference and then do the fitting and calculate covariance matrix for
> > last 30ns. This is done because I suspect that the average structure over
> > full trajectory will reflect all the changes occurring in the protein. It
> > also gives me low cosines (<0.1). The PCs show movement occurring in
> > certain regions of the protein.
> >
> > b. I take the average structure from the same window (last 30ns) then do
> > the fitting and calculate covariance matrix for the same. This is done
> with
> > an assumption that the reference structure must reflect the
> > equilibriated/stable part of the trajectory unlike the previous case.
> > Surprisingly it gives me high cosines (>0.5). Unlike the previous case,
> > this method shows very small movement in the protein (very low RMSF).
> >
> > Both of these methods give me different RMSF for the PCs although they
> are
> > done on the same part of the trajectory but the reference structure is
> > influencing the output.
> >
> >  Which protocol among the two is appropriate ?  And how can we explain
> high
> > cosines in second case where the reference structure is the average of
> the
> > same time window (there must not be large deviation) while I get low
> cosine
> > for the first case where deviations are calculated from the full
> trajectory
> > average (large deviation) ?
> >
> > Any help is appreciated.
> >
> > Thanks,
> >
> > -Vivek Modi
> > Graduate Student
> > IITK.
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>
>
> --
> *-----------------------
> Thanks and Regards,
> Bipin Singh*
>
>
> ------------------------------
>
>