[gmx-users] Principal Component Analysis
Gia Maisuradze
gia at chem.unr.edu
Tue Feb 22 20:55:51 CET 2005
Hi,
I am doing MD simulations and PCA for some mutants of lambda-repressor. The
time of simulations is 10ns. I have done two runs of MD simulations: in
first run I have used:
rlist = 0.8
coulombtype = cut-off
rcoulomb = 1.4
rvdw = 0.8
in mdp files, and in second run I have used:
rlist = 0.9
coulombtype = PME
rcoulomb = 0.9
fourierspacing = 0.12
pme_order = 4
rvdw = 0.9
ewald_rtol = 1e-5
When I have done PCA I have got the different behavior for first five
principal components. In both runs for slow folder mutant the cosine
contents are close to each other, and they are close to cosine. According to
the paper of Berk Hess (Phys. Rev. E, 62, 8438, 2000) in this case we have
the random diffusion. The cosine contents for both runs:
First run:
pc 1 - 0.9540
pc 2 - 0.0127
pc 3 - 0.0036
pc 4 - 0.0039
pc 5 - 0.0007
Second run:
pc 1 - 0.8246
pc 2 - 0.0485
pc 3 - 0.0007
pc 4 - 0.0038
pc 5 - 0.0148
For medium and fast folders the results are different. In first run for both
folders we have the resemblance to cosine for first five PCA, but in second
run the results are different. For medium folder I obtained following cosine
contents:
First run:
pc 1 - 0.8923
pc 2 - 0.0090
pc 3 - 0.0469
pc 4 - 0.0161
pc 5 - 0.0253
Second run:
pc 1- 0.5318
pc 2 - 0.2860
pc 3 - 0.0087
pc 4 - 0.0748
pc 5 - 0.0002
For fast folder:
First run:
pc 1 - 0.9658
pc 2 - 0.0002
pc 3 - 0.0167
pc 4 - 0.0045
pc 5 - 0.0048
Second run:
pc 1 - 0.4039
pc 2 - 0.2293
pc 3 - 0.1184
pc 4 - 0.0643
pc 5 - 0.0389
Consequently the mean square displacements (MSD) are different for these
runs. In first run for all mutants the behavior of MSD is similar to one
given in Hess's paper, we can see sub-diffusive and super-diffusive parts
for 1st principal component. In second run MSD of slow folder also has the
same behavior as in first run, but MSDs of medium and fast folders in second
run do not show super-diffusive part for first PC.
As I know the second MD run is more reliable than first one, but the results
of PCA from first run is "better". I was wondering what run is more
reliable, and why I got such a different results for PCA.
Thanks,
Gia Maisuradze
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