Dear Shantanu,
Unfortunately it is well documented that to reliably extract the
global parameters, data at 2 or more field strengths is required. For
a good review on this, see:
d'Auvergne E. J., Gooley P. R. (2007). Set theory formulation of the
model-free problem and the diffusion seeded model-free paradigm. Mol.
Biosyst., 3(7), 483-494. (http://dx.doi.org/10.1039/b702202f)
Or the Korzhnev 2001 review. The problem is that the analysis has
trouble distinguishing between the anisotropic and rhombic parts of
the diffusion tensor and internal motions, specifically chemical
exchange (see Tjandra, 1995) and nanosecond motions (see Schurr,
1994).
For the problems you are seeing of the spins being deselected, this
looks like structural data from the PDB has not been loaded for that
spin. This set up would not work though because when the diffusion
tensor is optimised (fixed=False), then the size or dimensionality of
the optimisation problem is the sum of diffusion tensor parameters and
the model-free parameters for each spin. This is incredibly large,
and a grid search would probably only complete after the end of the
universe.
To reliably obtain the ellipsoid tensor using only single field
strength data, you may need to develop new methodology or come up with
a new type of data to use in the analysis. This is one reason
Modelfree4 from Art Palmer cannot handle an ellipsoid tensor, the
program was originally designed with single field strength data in
mind. The best option though, if you really cannot collect the full
data set, would be to try with an initial diffusion tensor estimate
and then perform an iterative optimisation procedure, similar to that
described in:
d'Auvergne, E. J. and Gooley, P. R. (2008). Optimisation of NMR
dynamic models II. A new methodology for the dual optimisation of the
model-free parameters and the Brownian rotational diffusion tensor. J.
Biomol. NMR, 40(2), 121-133. (http://dx.doi.org/10.1039/b702202f).
Some literature research would have to be done for the technique. So
more references that go into these problems are given at
http://www.nmr-relax.com/refs.html. I'm sorry if this was not of much
help.
Regards,
Edward
On 27 May 2011 09:37, Shantanu S. Bhattacharyya Mr <shantanu01@xxxxxxx> wrote:
Hello,
I am sorry if my question is too basic but I am trying to get the global
parameters to describe the dynamics of my protein and I am not really
looking for any spin specific parameters. I have data only at 600 MHz.
I thought I could run the model-free.py script using
diffusion_tensor.init((9e-8, 0.5, 0.3, 60, 290, 100), fixed=False)
But then I get :
Over-fit spin deselection.
RelaxWarning: The spin ':0' has been deselected because of missing
structural data.
RelaxWarning: The spin ':1' has been deselected because of missing
structural data.
RelaxWarning: The spin ':2' has been deselected because of missing
structural data.
RelaxWarning: The spin ':3' has been deselected because of missing
structural data.
RelaxWarning: The spin ':4' has been deselected because of missing
structural data.
RelaxWarning: The spin ':5' has been deselected because of missing
structural data.
and so on for all my 75 residues.
I dont think I can use
#diffusion_tensor.init(10e-9, fixed=false)
because it complains of a very massive grid search which cannot be run.
Is there an easier way to optimise the tm or is there an entirely
different approach to get the global parameters for a molecule ?
Any guidance will be helpful.
Thanks for your time.
--
Shantanu S. Bhattacharyya
Grad Student, Biological Sciences
Carnegie Mellon University
url : http://esesbee.com
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Re: Determine global parameters