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J Biomol NMR. 2007 Aug;38(4):303-13. Epub 2007 Jun 26.

Top-down approach in protein RDC data analysis: de novo estimation of the alignment tensor.

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  • 1Laboratory of Molecular Biophysics, National Heart, Lung, and Blood Institute, National Institutes of Health, Building 50, Room 3503, Bethesda, MD 20892, USA.


In solution NMR spectroscopy the residual dipolar coupling (RDC) is invaluable in improving both the precision and accuracy of NMR structures during their structural refinement. The RDC also provides a potential to determine protein structure de novo. These procedures are only effective when an accurate estimate of the alignment tensor has already been made. Here we present a top-down approach, starting from the secondary structure elements and finishing at the residue level, for RDC data analysis in order to obtain a better estimate of the alignment tensor. Using only the RDCs from N-H bonds of residues in alpha-helices and CA-CO bonds in beta-strands, we are able to determine the offset and the approximate amplitude of the RDC modulation-curve for each secondary structure element, which are subsequently used as targets for global minimization. The alignment order parameters and the orientation of the major principal axis of individual helix or strand, with respect to the alignment frame, can be determined in each of the eight quadrants of a sphere. The following minimization against RDC of all residues within the helix or strand segment can be carried out with fixed alignment order parameters to improve the accuracy of the orientation. For a helical protein Bax, the three components A(xx), A(yy) and A(zz), of the alignment order can be determined with this method in average to within 2.3% deviation from the values calculated with the available atomic coordinates. Similarly for beta-sheet protein Ubiquitin they agree in average to within 8.5%. The larger discrepancy in beta-strand parameters comes from both the diversity of the beta-sheet structure and the lower precision of CA-CO RDCs. This top-down approach is a robust method for alignment tensor estimation and also holds a promise for providing a protein topological fold using limited sets of RDCs.

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