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From: Jason Swails <jason.swails.gmail.com>

Date: Tue, 22 Nov 2016 12:26:31 -0500

On Tue, Nov 22, 2016 at 9:54 AM, The Cromicus Productions <

thecromicusproductions.gmail.com> wrote:

*> Hi everyone!
*

*> I'm able to compute the principal components of a given trajectory using
*

*> PCAsuite.
*

*> http://mmb.pcb.ub.es/software/pcasuite/pcasuite.html
*

*> Then, I can convert them into pdb files and watch the motions.
*

*> PCAsuite also gives me the eigenvalues, so I know which are the most
*

*> important.
*

*> Now, if I understand correctly, the principal components are some "chosen"
*

*> normal modes which summarize the information of the trajectory, but how do
*

*> I know which normal mode is associated to each component I get? In
*

*> particular, I would like to know what is the associated vibration frequency
*

*> of each of the components.
*

*>
*

â€‹â€‹

â€‹PCA and normal modes are very different. The "modes" in PCA are

eigenvectors of the covariance matrix. The modes in NMA are eigenvectors

of the Hessian matrix. They *can* contain similar information, but there

is not a 1:1 correlation between PCA modes and normal modes.â€‹ There are

large operational differences, too -- for instance, PCA requires an

ensemble of 'snapshots' (a rather *large* ensemble), whereas NMA requires a

single *minimized* structure.

Using PCA (more specifically using the mass-weighted covariance matrix

rather than the standard covariance matrix) as approximations of

vibrational modes is referred to as the "quasi-harmonic approximation". I

would suggest starting there and scanning the literature.

HTH,

Jason

Date: Tue, 22 Nov 2016 12:26:31 -0500

On Tue, Nov 22, 2016 at 9:54 AM, The Cromicus Productions <

thecromicusproductions.gmail.com> wrote:

â€‹â€‹

â€‹PCA and normal modes are very different. The "modes" in PCA are

eigenvectors of the covariance matrix. The modes in NMA are eigenvectors

of the Hessian matrix. They *can* contain similar information, but there

is not a 1:1 correlation between PCA modes and normal modes.â€‹ There are

large operational differences, too -- for instance, PCA requires an

ensemble of 'snapshots' (a rather *large* ensemble), whereas NMA requires a

single *minimized* structure.

Using PCA (more specifically using the mass-weighted covariance matrix

rather than the standard covariance matrix) as approximations of

vibrational modes is referred to as the "quasi-harmonic approximation". I

would suggest starting there and scanning the literature.

HTH,

Jason

-- Jason M. Swails _______________________________________________ AMBER mailing list AMBER.ambermd.org http://lists.ambermd.org/mailman/listinfo/amberReceived on Tue Nov 22 2016 - 09:30:03 PST

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