Hi, This problem you have encountered is that of artificial chemical exchange. This is quite well documented by Tjandra et al., 1995. The instability has been compounded by the use of only single field strength data as the physics theory cannot differentiate between Rex (which scales quadratically with field strength assuming fast exchange) and the global correlation times (which are field strength invariant). I would recommend also reading the following article:
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. This article is linked from here: http://www.nmr-relax.com/refs.html. In this paper I fully describe all of the issues you are seeing here, covering all details and possible solutions. I hope this helps. If you have any questions from this paper, please don't hesitate to ask. Regards, Edward On Thu, Jan 8, 2009 at 4:43 PM, Pierre-Yves Savard <[email protected]> wrote: > Hello, > > I have some trouble using relax with my data. > > I have data at 600 MHz only so I use models m0,m1,m2,m3,m9 with the > classic approach of starting with an initial estimate of the Tm, with a > modified versiion of the script mf_multimodel.py. which includes model > selection and diffusion tensor optimization. > > The first problem is that it doesn't converge. However, the second > problem is more important in that, following the different iterations, > the Tm and S2 go down and the Rex go up to values approaching the R2. > After 35 iterations, the Tm is less than half that estimated with the > R2/R1 ratio (using quadric or tensor2) and almost all residues are > fitted with model m3... This problem starts at the second iteration. > > I used this approach with success using a sample of the same protein > (136 residues) with a slightly different concentration. Using the data > from this sample (which are very close to the problematic dataset), the > converged tm was very close to the estimated tm based on the R2/R1 > ratio... Moreover, S2 were much higher, with a mean value of 0.8, with > only a few Rex... > > Sample one (good results): Estimated Tm = 10.1 ns, converged Tm = 10.1, > S2 = 0.88, 8 residues with Rex (mean of 2 s-1). > > Sample two (problematic): Estimated Tm = 10.09 ns, Tm after 35 iteration > = 4.30, S2 = 0.48, 102 residues with Rex (mean of 10.1 s-1). > > Any idea why the second sample gives rise to such annoying results ? > > Thanks a lot, > > > Pierre-Yves > > -- > Pierre-Yves Savard > Professionnel de recherche > Département de biochime et de microbiologie > ------------------------------------------- > Pavillon Charles-Eugène Marchand, local3252 > 1030 avenue de la médecine > Université Laval, Québec, Qc, G1V 0A6 > Tél: 418.656.2131 #4530 Fax: 418.656.7176 > [email protected] > ------------------------------------------- > > > _______________________________________________ > relax (http://nmr-relax.com) > > This is the relax-users mailing list > [email protected] > > To unsubscribe from this list, get a password > reminder, or change your subscription options, > visit the list information page at > https://mail.gna.org/listinfo/relax-users > _______________________________________________ relax (http://nmr-relax.com) This is the relax-users mailing list [email protected] To unsubscribe from this list, get a password reminder, or change your subscription options, visit the list information page at https://mail.gna.org/listinfo/relax-users
