Hi,
On Sat, Feb 20, 2016 at 4:10 PM, Joel Lapin <jlapin.ncsu.edu> wrote:
> matrix. My understanding of analyzing this matrix is that the largest
> eigenvalues are your most significant degrees of freedom, which is simple
> enough. The only issue is that the eigenvalues are perfectly sorted, which
> doesn't make much sense to me. This would imply that the majority of
> fluctuation in my protein happens at one end, while little to no
> fluctuation happens in the rest of the protein.
That's not really how you should interpret your eigenvectors. The
eigenvectors when calculated from a coordinate covariance matrix
describe *collective motions* in your system; the eigenvector
associated with the largest eigenvalue is the motion with the biggest
variance, the second largest eigenvalue the motion with the
second-largest variance, and so on. It's not necessarily localized to
a certain part of your system, although it could be. To know for
certain you can either visualize a particular eigenvector (aka
principal component in this case) with 'modes trajout', look at a
"porcupine" visualization via the NMwiz plugin for VMD with
'diagmatrix nmwiz' output, or look at where fluctuations are occurring
with output from 'modes fluct' etc.
Hope this helps,
-Dan
>
> Can someone please help me physically interpret this covariance matrix in
> terms of which degrees of freedom are most significant in my protein?
>
> Thank you
> Joel
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--
-------------------------
Daniel R. Roe, PhD
Department of Medicinal Chemistry
University of Utah
30 South 2000 East, Room 307
Salt Lake City, UT 84112-5820
http://home.chpc.utah.edu/~cheatham/
(801) 587-9652
(801) 585-6208 (Fax)
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Received on Sat Feb 20 2016 - 16:00:04 PST
