Alex
On 10/5/06, Edward d'Auvergne <[EMAIL PROTECTED]> wrote:
That's a good idea, the eigenvector of the CSA tensor perpendicular to
the base rings and parallel to the long axis of the diffusion tensor
should contain a bit of that missing information about Da. Is the
amplitude of the perpendicular CSA component (say sigma_z)
significantly different from the other two eigenvalues (sigma_x and
sigma_y)? relax is currently incapable of using that information
though. Maybe that will soon change ;)
Edward
On 10/6/06, Alexandar Hansen < [EMAIL PROTECTED]> wrote:
> I had meant to say more on this but had to run to a meeting.
>
> In addition to ribose residues being helpful, the 13C CSA tensors of the
> base are highly asymetric and anisotropic. One of the components of the CSA
> tensor is perpindicular to the plane of the base (I think, perhaps, 13CO has
> a similar situation?) so that the CSA part of the relaxation will be
> sensitive to both orientations and should help to adequately span the 3D
> environment of anisotropic diffusion tensors. We have shown this to be true
> when measuring residual CSAs (RCSAs) as complementary to RDCs (Me, JMR
> (2006) 179, p323)
>
> Alright, off to another meeting!
>
>
> Alex
>
>
>
> On 10/4/06, Alexandar Hansen <[EMAIL PROTECTED] > wrote:
> > You have it right. Measuring ribose, or simply anything that's not also
> perpindicular to the base, should adequately sample more of the 3D space.
> We find this to be the case frequently when analyzing RDCs measured in RNA.
> Of particular interest would be the C1'-H1's. Having just a handful of
> those would like be highly beneficial.
> >
> > Alex
> >
> >
> >
> >
> > On 10/4/06, Edward d'Auvergne < [EMAIL PROTECTED]> wrote:
> > > Hi,
> > >
> > > In relaxation data analysis, you can only view the components of the
> > > Brownian rotational diffusion tensor that the XH bond vectors sample.
> > > So if your macromolecule diffuses as a prolate spheroid but the XH
> > > bond vectors are close to perpendicular to the unique axis of the
> > > tensor, the only component of the diffusion tensor that the relaxation
> > > data contains information about is the eigenvalue Dper (the
> > > perpendicular component of the tensor). The result is that the
> > > diffusion will appear to be spherical where Diso has the value of
> > > Dper! In relax the parameters tm (which is essentially Diso) and Da
> > > are optimised. For this case, Da (and hence Dratio) would be
> > > undefined - it can have any geometrically possible value while having
> > > zero effect on the results.
> > >
> > > Have you tried starting with the calculated Da value (or Dratio if you
> > > wish)? This is not possible using the 'full_analysis.py' script, but
> > > the other sample scripts can be modified to do this. As these
> > > parameters will be statistically undefined, the final optimised values
> > > should be pretty close to the input values. This assumes tm (or Diso)
> > > is set to be close to the Dper value as the curvature of the space may
> > > cause optimisation to shift Da. The parameter Dr would also be
> > > undefined and this would fully explain the Dr value of 1 reported in
> > > bug #7297 ( https://gna.org/bugs/?7297 ).
> > >
> > > The problem of the undefined Da and Dr, and hence the molecule
> > > appearing to diffuse as a sphere, could be resolved by having a few
> > > vectors which deviate from the perpendicular. However this is only
> > > important if you are actually interested in characterising the
> > > Brownian rotational diffusion. In any case, attempting to optimise
> > > these values using relaxation data of perpendicular XH's will only
> > > result in statistically insignificant values - it's not statistically
> > > possible to pull out these parameters. It is almost guaranteed that
> > > AIC model selection will select spherical diffusion. Would the ribose
> > > CH's together with the base XH's adequately sample three-dimensional
> > > space?
> > >
> > > I hope this info helps,
> > >
> > > Edward
> > >
> > >
> > >
> > > On 10/5/06, Alexandar Hansen < [EMAIL PROTECTED]> wrote:
> > > > Hello all,
> > > >
> > > > In studying RNA you run into a number of limiting factors of your data
> set.
> > > > a) NH data is available only on half of the residues (G's and U's), b)
> these
> > > > G's and U's must be in a helix, or the NH becomes exchanged with
> solvent,
> > > > and c) the NH vectors on the bases in a helix don't sample space
> randomly
> > > > and are oriented ~perpindicular to the diffusion axis (RNA is almost
> always
> > > > prolate shaped). This last scenario, for you protein folks, would be
> > > > similar to the situation where you had a single alpha helix and only
> NH
> > > > data, ie. sample only directions paralell to the helix axis.
> > > >
> > > > With this in mind, one can easily imagine that any relaxation analysis
> would
> > > > be happy to fit them to a lower diffusion model, such as spherical,
> than
> > > > what is in reality highly anisotropic. What I'd like to know how to
> do is
> > > > impose additional limits on the minimization step such that, for
> instance,
> > > > the Dratio could be fixed between some values. With the data I've
> been
> > > > analyzing, relax happily fits my NH data to the spherical case and,
> for the
> > > > prolate model, fits the Dratio to 1 -> 1.1. From hydrodynamic
> simulation,
> > > > we know, however, that the Dratio should be between 4-5. Are there
> any
> > > > thoughts on how to do this? On one level, it appears to be forcing
> the data
> > > > into a particular model. But if you can know something about the
> diffusion
> > > > parameters or anything else a priori from a different source than NMR,
> > > > shouldn't that be allowed to factor into the analysis?
> > > >
> > > > Thanks,
> > > > Alex Hansen
> > > >
> > > >
> > > > _______________________________________________
> > > > relax ( http://nmr-relax.com)
> > > >
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> > > >
> > >
> >
> >
> >
>
>
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