[gmx-users] eigenvalues

[Monika Sharma]

Hi.
As far as I know, PCA analysis breaks your total motion in system, or rather
decouples it into respective motions. And by the eigenvectors and the
corresponding eigenvalues it means that this 1st vector or the 2nd vector
contributes this percent of the total motion. It is system-dependent. Is
this really related to the difference in the degrees of freedom of two
different systems (that I am a bit skeptic about) with which you are
confusing it now.
If I am missing something here, then anyone please correct me.
Regards,
Monika

On Thu, Jan 8, 2009 at 4:31 PM, <sanjay23 at iitb.ac.in> wrote:

> dear gromacs users,
>
> i did PCA analysis for my trajectory using g_covar and g_anaeig, i have
> taken trajectory of 25ns from both protein alone and protein_withligands(i
> did two simulation one with ligands and other by removing the ligands from
> pdb file)and extracted eigenvalues along first 10 eigenvector, when i
> compared eigenvalues i find that protein_withligands has high values in
> compare to protein alone,  but from literature protein alone is more
> flexible structure and after ligand binding it changes in to more rigid
> structure. primary analysis like RMSD, RMSF calculation showing high
> values for protein alone in compare to protien_withligands. i think i
> should also get higher eigenvalue for protein alone.. is any thing wrong
> with my trajectory. i had used same mdp file for both simulation. i am
> sending values of Ist 10 eigenvector for make my question more clear. any
> suggestion is appreciable
> protein-withligands
> 1 1.48497
> 2 0.674994
> 3 0.410547
> 4 0.279636
> 5 0.237182
> 6 0.213209
> 7 0.158359
> 8 0.140052
> 9 0.126227
> 10 0.113618
>
> protein alone
> 1 0.526848
> 2 0.351471
> 3 0.267247
> 4 0.248945
> 5 0.222829
> 6 0.204475
> 7 0.158441
> 8 0.12583
> 9 0.0970591
> 10 0.0923962
>
>
>
> thanks
> sanjay
>
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