NDLI: Structure-based protein NMR assignments using native structural ensembles

Content Provider	Springer Nature Link
Author	Apaydın, Mehmet Serkan Conitzer, Vincent Donald, Bruce Randall
Copyright Year	2008
Abstract	An important step in NMR protein structure determination is the assignment of resonances and NOEs to corresponding nuclei. Structure-based assignment (SBA) uses a model structure (“template”) for the target protein to expedite this process. Nuclear vector replacement (NVR) is an SBA framework that combines multiple sources of NMR data (chemical shifts, RDCs, sparse NOEs, amide exchange rates, TOCSY) and has high accuracy when the template is close to the target protein’s structure (less than 2 Å backbone RMSD). However, a close template may not always be available. We extend the circle of convergence of NVR for distant templates by using an ensemble of structures. This ensemble corresponds to the low-frequency perturbations of the given template and is obtained using normal mode analysis (NMA). Our algorithm assigns resonances and sparse NOEs using each of the structures in the ensemble separately, and aggregates the results using a voting scheme based on maximum bipartite matching. Experimental results on human ubiquitin, using four distant template structures show an increase in the assignment accuracy. Our algorithm also improves the robustness of NVR with respect to structural noise. We provide a confidence measure for each assignment using the percentage of the structures that agree on that assignment. We use this measure to assign a subset of the peaks with even higher accuracy. We further validate our algorithm on data for two additional proteins with NVR. We then show the general applicability of our approach by applying our NMA ensemble-based voting scheme to another SBA tool, MARS. For three test proteins with corresponding templates, including the 370-residue maltose binding protein, we increase the number of reliable assignments made by MARS. Finally, we show that our voting scheme is sound and optimal, by proving that it is a maximum likelihood estimator of the correct assignments.
Starting Page	263
Ending Page	276
Page Count	14
File Format	PDF
ISSN	09252738
Journal	Journal of Biomolecular NMR
Volume Number	40
Issue Number	4
e-ISSN	15735001
Language	English
Publisher	Springer Netherlands
Publisher Date	2008-03-26
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Automated NMR assignments Normal mode analysis NMR structural biology Protein flexibility via structural ensembles Structural bioinformatics Biochemistry Polymer Sciences Biophysics/Biomedical Physics
Content Type	Text
Resource Type	Article
Subject	Spectroscopy Biochemistry

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