analysis of limited data sets -- October 04, 2006 - 16:16

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