[gmx-users] eigenvalues

[Tsjerk Wassenaar]

Hi,

Well, the trace of the covariance matrix (thus the sum of the
eigenvectors), should say something about overall flexibility. In that
case, the observation that the protein with ligand seems more flexible
than without is not completely incorrect. However, the question arises
regarding the nature of flexibility. Unless you have a perfectly
equilibrated system, the assessment of flexibility using covariance
analysis also includes a conformational drift. You can check
equilibration by looking at the cosine content of the pc's.
Another thing that matters is the structure you use for fitting, which
also influences results from RMSD/RMSF.

I don't know how large your system is, but you might try and do the
covariance analysis on the last 10 ns. For very large systems,
equilibration will likely take even longer.

Hope it helps,

Tsjerk


On Thu, Jan 8, 2009 at 12:33 PM, Xavier Periole <X.Periole at rug.nl> wrote:
> On Thu, 8 Jan 2009 16:31:01 +0530 (IST)
>  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
>
> The eigenvalues alone do not mean much. They probably do not correspond to
> the same eigenvectors. You have to compare the eigenvectors from the two
> simulations. This is possible using a RMSIP (root mean square inner
> product).
> You'll find the definition and more details in papers from Amadei and
> Ceruso.
> hints: Amadei et al., 1999; Ceruso et al., 1999a,b, 2003; Merlino et al.,
> 2003; Roccatano et al., 2003
>
> Best,
> XAvier.
>>
>> 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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>
> -----------------------------------------------------
> XAvier Periole - PhD
>
> - Molecular Dynamics Group -
> Computation and NMR
> University of Groningen
> The Netherlands
> -----------------------------------------------------
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-- 
Tsjerk A. Wassenaar, Ph.D.
Junior UD (post-doc)
Biomolecular NMR, Bijvoet Center
Utrecht University
Padualaan 8
3584 CH Utrecht
The Netherlands
P: +31-30-2539931
F: +31-30-2537623