Hello Santhos-- My apologies for being slow to reply.
> I have a question regarding the usage of RSCA as validation dataset and hoping > you could shed some light on this. > > I have followed the details presented in "Validation of Protein Structure from > Anisotropic Carbonyl Chemical Shifts in a Dilute Liquid Crystalline Phase" in > Jacs 1998, 120, 6836 which used chemical shift anisotropies as validation data > for 1d3z nmr structure of Ubiquitin and also the recent paper introducing > 2MJB. > > The chemical shift tensor orientation for Carbonyl atoms are dependent upon > the > beta angle it makes to the CN bond vector while N and HN depend upon the bond > vector orientation of NH. (Jacs 2000, 122, 10143). > > Since RDC's also contain information about bond vector orientations, any > structure/ensemble that is optimized with CN, NH RDC data could also optimize > the > RCSA.This along with the observation that alignment tensors of Ubiquitin are > very > similar (they take one of the 2 orientations in my calculations and one of > your > papers), makes RCSA a very weak validation dataset. Am I missing something in > my > observations? How can one justify RSCA as cross-validation data? Certainly the CSA data thus validate the results obtained with RDCs- showing that improvements are not simply fits to noise. Moreover, the results place limits on dynamics, as the timescales allowed by CSAs may well differ from those of RDCs. > > I have observed one small glitch in the documentation of XPLOR-NIH, > in varTensorTools. normalizedScalarProduct(t1,t2) : t1, t2 should be the > tensor > objects instead of RDCpot. > (http://nmr.cit.nih.gov/xplor-nih/doc/current/python/ > ref/varTensorTools.html). Sorry if it was obvious. > Thanks for the note. It is corrected for the next release. best regards-- Charles _______________________________________________ Xplor-nih mailing list [email protected] https://dcb.cit.nih.gov/mailman/listinfo/xplor-nih
