An expectation/maximization nuclear vector replacement algorithm for automated NMR resonance assignments

High-throughput NMR structural biology can play an important role in structural genomics. We report an automated procedure for high-throughput NMR resonance assignment for a protein of known structure, or of a homologous structure. These assignments are a pre-requisite for probing protein–protein interactions, protein–ligand binding, and dynamics by NMR. Assignments are also the starting point for structure determination and refinement. A new algorithm, called Nuclear Vector Replacement (NVR) is introduced to compute as-signments that optimally correlate experimentally measured NH residual dipolar couplings (RDCs) to a given a priori whole-protein 3D structural model. The algorithm requires only uniform 15N-labeling of the protein and processes unassigned HN-15N HSQC spectra, HN-15N RDCs, and sparse HN-HN NOE’s (dNNs), all of which can be acquired in a fraction of the time needed to record the traditional suite of experiments used to perform resonance assign-ments. NVR runs in minutes and efficiently assigns the (HN,15N) backbone resonances as well as the dNNs of the 3D 15N-NOESY spectrum, in O(n3) time. The algorithm is demonstrated on NMR data from a 76-residue protein, human ubiquitin, matched to four structures, in