Structure-based protein NMR assignments using native structural ensembles

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 A 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.

Structure-Based Assignment of Ile, Leu, and Val Methyl Groups in the Active and Inactive Forms of the Mitogen-Activated Protein Kinase Extracellular Signal-Regulated Kinase 2

“…Thus, various mathematical methods have been applied to help overcome this problem, including graph theory, fuzzy math/logic, nuclear vector representation, clustering algorithms, and probabilistic techniques. 12,13,15,17,18,59–62 A number of programs have been developed for automated structure-based assignment of methyl resonances, including MAP-XS (II), 13,17 FLAMEnGO(2.0), 15,18 and a PRE-based program. 63 All these programs first employ residue-type identification to reduce the complexity of the search and then employ NOE and/or PRE constraints as their primary experimental data.…”

“…10–12 Various programs have been developed for structure-based methyl resonance assignment in proteins that combine the structural data with experimental data and theoretical information including distance information obtained from NOESY and/or paramagnetic relaxation enhancement (PRE) experiments, predictions of the 1 H and 13 C chemical shifts of methyl groups, labeling strategies that allow identification of residue-type or stereospecific assignment of methyls. 9,13–20 Methods that employ PRE data require production of multiple constructs or mutant proteins, which is challenging for proteins that are not highly expressed in isotopically labeled media.…”

NVR-BIP: Nuclear Vector Replacement using Binary Integer Programming for NMR Structure-Based Assignments

“…As future work, we plan to extend our approach to handle extra peaks as well. To handle extra peaks and to achieve robustness against noise, one possibility is to use Normal Mode Analysis to obtain an ensemble of protein structures and to combine the assignments for each of these structures using a voting scheme as in [13]. …”

“…This resulted in improved assignment accuracy for distant templates of target proteins. A recent study [13] used Normal ModeAnalysis to further augment the accuracy of NVR for distant structural templates.…”

An ant colony optimization approach for solving the nuclear magnetic resonance structure based assignment problem

“…These data types provide side chain proton chemical shifts and solvent accessibility information of the labile protons, respectively, and allow the determination of the amino acid type as well as whether the proton is exposed to the solvent or not, respectively. This resulted in improved assignment accuracies for distant templates of target proteins [3].…”