ORIUM: Optimized RDC-based iterative and unified model-free analysis.

Residual dipolar couplings (RDCs) are NMR parameters that provide both structural and dynamic information concerning inter-nuclear vectors, such as N-H-N and C alpha-H alpha bonds within the protein backbone. Two approaches for extracting this information from RDCs are the model free analysis (MFA) (Meiler et al. in J Am Chem Soc 123:6098-6107, 2001; Peti et al. in J Am Chem Soc 124:5822-5833, 2002) and the direct interpretation of dipolar couplings (DIDCs) (Tolman in J Am Chem Soc 124:12020-12030, 2002). Both methods have been incorporated into iterative schemes, namely the self-consistent RDC based MFA (SCRM) (Lakomek et al. in J Biomol NMR 41:139-155, 2008) and iterative DIDC (Yao et al. in J Phys Chem B 112:6045-6056, 2008), with the goal of removing the influence of structural noise in the MFA and DIDC formulations. Here, we report a new iterative procedure entitled Optimized RDC-based Iterative and Unified Model-free analysis (ORIUM). ORIUM unifies theoretical concepts developed in the MFA, SCRM, and DIDC methods to construct a computationally less demanding approach to determine these structural and dynamic parameters. In all schemes, dynamic averaging reduces the actual magnitude of the alignment tensors complicating the determination of the absolute values for the generalized order parameters. To readdress this scaling issue that has been previously investigated (Lakomek et al. in J Biomol NMR 41:139-155, 2008; Salmon et al. in Angew Chem Int Edit 48:4154-4157, 2009), a new method is presented using only RDC data to establish a lower bound on protein motion, bypassing the requirement of Lipari-Szabo order parameters. ORIUM and the new scaling procedure are applied to the proteins ubiquitin and the third immunoglobulin domain of protein G (GB3). Our results indicate good agreement with the SCRM and iterative DIDC approaches and signify the general applicability of ORIUM and the proposed scaling for the extraction of inter-nuclear vector structural and dynamic content