Empirical correlation between protein backbone 15N and 13C secondary chemical shifts and its application to nitrogen...

The linear analysis of chemical shifts (LACS) has provided a robust method for identifying and correcting 13C chemical shift referencing problems in data from protein NMR spectroscopy. Unlike other approaches, LACS does not require prior knowledge of the three-dimensional structure or inference of the secondary structure of the protein. It also does not require extensive assignment of the NMR data. We report here a way of extending the LACS approach to 15N NMR data from proteins, so as to enable the detection and correction of inconsistencies in chemical shift referencing for this nucleus. The approach is based on our finding that the secondary 15N chemical shift of the backbone nitrogen atom of residue i is strongly correlated with the secondary chemical shift difference (experimental minus random coil) between the alpha and beta carbons of residue i-1. Thus once alpha and beta 13C chemical shifts are available (their difference is referencing error-free), the 15N referencing can be validated, and an appropriate offset correction can be derived. This approach can be implemented prior to a structure determination and can be used to analyze potential referencing problems in database data not associated with three-dimensional structure. Application of the LACS algorithm to the current BMRB protein chemical shift database, revealed that nearly 35% of the BMRB entries have delta 15N values mis-referenced by over 0.7 ppm and over 25% of them have delta 1HN values mis-referenced by over 0.12 ppm. One implication of the findings reported here is that a backbone 15N chemical shift provides a better indicator of the conformation of the preceding residue than of the residue itself.