tsjerkw at gmail.com
Tue Aug 16 10:27:07 CEST 2011
> First, is there anyway to specify that the covar.dat output will be in R
> distance (meaning sqrt(x^2+y^2+Z^2)) and not in separate Cartesian
> coordinates? also when examining the output I don't understand how the main
> diagonal values are different than 1, for instance the x1x1
> covariance should be 1.. or am I missing something?
No, that is quite a different thing. But g_rms -rmsdist does just that :)
Then, the diagonal entries are variances/fluctuations, not
self-correlations, which are unity by definition.
> Second, Say I would like to analyze the main difference between two
> trajectories of the same protein using PCA. is it KOSHER to use the same
> first frame which is identical between both runs as the reference strucutre
> and then just append both runs into a single trajectory and then use g_covar
> to analyse the subsequent conformations? if not, how would one go about
> comparing the PC's of two different trajectories? other than dumping all the
> frames in gro/pdb format and running the analysis in another program (such
> as MATLAB)
Fitting all to the same reference is fine. Then calculating the
principal components on the concatenated trajectory is what is
sometimes called 'combined essential dynamics'. But it's not good for
comparing principal components. It will give one set of components for
all frames and allows you to compare the projections of the separate
trajectories onto these components, from which you can infer in how
far they sample the same or different subspaces. To compare the
eigenvectors, you need to calculate components on the separate
trajectories, fitting each onto the same reference. The sets of
principal components can then be used to calculate the overlap between
the subspaces sampled. Check the manpage for g_anaeig.
Hope it helps,
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Tsjerk A. Wassenaar, Ph.D.
Molecular Dynamics Group
* Groningen Institute for Biomolecular Research and Biotechnology
* Zernike Institute for Advanced Materials
University of Groningen
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