scholarly journals Complete protein assignment from sets of spectra recorded overnight

2019 ◽  
Vol 73 (1-2) ◽  
pp. 59-70
Author(s):  
Jonas Fredriksson ◽  
Wolfgang Bermel ◽  
Martin Billeter
Keyword(s):  
Input Data ◽  
Protein Nmr ◽  
Pulse Sequences ◽  
Side Chain ◽  
Sequential Assignment ◽  
Triple Resonance ◽  
Recording Time ◽  
Protein Assignment ◽  
Complete Protein ◽  
Joint Decomposition

Abstract A flexible and scalable approach for protein NMR is introduced that builds on rapid data collection via projection spectroscopy and analysis of the spectral input data via joint decomposition. Input data may originate from various types of spectra, depending on the ultimate goal: these may result from experiments based on triple-resonance pulse sequences, or on TOCSY or NOESY sequences, or mixtures thereof. Flexible refers to the free choice of spectra for the joint decompositions depending on the purpose: assignments, structure, dynamics, interactions. Scalable means that the approach is open to the addition of similar or different experiments, e.g. larger proteins may require a wider selection of triple-resonance based experiments. Central to the proposed approach is the mutual support among the different spectra during the spectral analysis: for example, sparser triple-resonance spectra may help decomposing (separating) spin systems in a TOCSY or identifying unique NOEs. In the example presented, backbone plus side chain assignments of ubiquitin were obtained from the combination of either two or three of the following projection experiments: a 4D HCCCONH, a 4D HNCACO and a 3D HNCACB. In all cases, TOCSY data (4D HCCCONH) proved crucial not only for the side chain assignments, but also for the sequential assignment. Even when total recording time was reduced to about 10 h, nearly complete assignments were obtained, with very few missing assignments and even fewer differences to a reference.

Double and Triple Resonance NMR Methods for Protein Assignment

2003 ◽  
pp. 29-52 ◽  
Author(s):  
Brian Whitehead ◽  
C. Jeremy Craven ◽  
Jonathan P. Waltho
Keyword(s):  
Triple Resonance ◽  
Triple Resonance Nmr ◽  
Protein Assignment ◽  
Nmr Methods

NMR spectroscopy: a multifaceted approach to macromolecular structure

2000 ◽  
Vol 33 (1) ◽  
pp. 29-65 ◽  
Author(s):  
Ann E. Ferentz ◽  
Gerhard Wagner
Keyword(s):  
Nmr Spectroscopy ◽  
Structure Determination ◽  
Solution Structure ◽  
Residual Dipolar Couplings ◽  
Complete Solution ◽  
Protein Structures ◽  
Sequential Assignment ◽  
Resonance Spectroscopy ◽  
Triple Resonance ◽  
Membrane Bound

1. Introduction 292. Landmarks in NMR of macromolecules 322.1 Protein structures and methods development 322.1.1 Sequential assignment method 322.1.2 Triple-resonance experiments 342.1.3 Structures of large proteins 362.2 Protein–nucleic acid complexes 372.3 RNA structures 382.4 Membrane-bound systems 393. NMR spectroscopy today 403.1 State-of-the-art structure determination 413.2 New methods 443.2.1 Residual dipolar couplings 443.2.2 Direct detection of hydrogen bonds 443.2.3 Spin labeling 453.2.4 Segmental labeling 463.3 Protein complexes 473.4 Mobility studies 503.5 Determination of time-dependent structures 523.6 Drug discovery 534. The future of NMR 544.1 The ease of structure determination 544.2 The ease of making recombinant protein 554.3 Post-translationally modified proteins 554.4 Approaches to large and/or membrane-bound proteins 564.5 NMR in structural genomics 564.6 Synergy of NMR and crystallography in protein structure determination 565. Conclusion 576. Acknowledgements 577. References 57Since the publication of the first complete solution structure of a protein in 1985 (Williamson et al. 1985), tremendous technological advances have brought nuclear magnetic resonance spectroscopy to the forefront of structural biology. Innovations in magnet design, electronics, pulse sequences, data analysis, and computational methods have combined to make NMR an extremely powerful technique for studying biological macromolecules at atomic resolution (Clore & Gronenborn, 1998). Most recently, new labeling and pulse techniques have been developed that push the fundamental line-width limit for resolution in NMR spectroscopy, making it possible to obtain high-field spectra with better resolution than ever before (Dötsch & Wagner, 1998). These methods are facilitating the study of systems of ever-increasing complexity and molecular weight.

Assignment of the side-chain proton and carbon-13 resonances of interleukin-1.beta. using double- and triple-resonance heteronuclear three-dimensional NMR spectroscopy

Biochemistry ◽  
1990 ◽  
Vol 29 (35) ◽  
pp. 8172-8184 ◽  
Author(s):  
G. Marius Clore ◽  
Ad Bax ◽  
Paul C. Driscoll ◽  
Paul T. Wingfield ◽  
Angela M. Gronenborn
Keyword(s):  
Nmr Spectroscopy ◽  
Interleukin 1 ◽  
Three Dimensional ◽  
Side Chain ◽  
Triple Resonance ◽  
Interleukin 1 Beta

The signs of the side-chain spin couplings in furanaldehydes as determined by nuclear magnetic triple resonance

1963 ◽  
Vol 11 (1-6) ◽  
pp. 454-464 ◽  
Author(s):  
Ragnar A. Hoffman ◽  
Bo Gestblom ◽  
Salo Gronowitz ◽  
Sture Forsén
Keyword(s):  
Side Chain ◽  
Triple Resonance ◽  
Nuclear Magnetic

GASA: A GRAPH-BASED AUTOMATED NMR BACKBONE RESONANCE SEQUENTIAL ASSIGNMENT PROGRAM

2007 ◽  
Vol 05 (02a) ◽  
pp. 313-333 ◽  
Author(s):  
XIANG WAN ◽  
GUOHUI LIN
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Protein Nmr ◽  
Three Dimensional ◽  
Protein Structure Determination ◽  
Spin Systems ◽  
Sequential Assignment ◽  
Amino Acid Residues ◽  
Backbone Resonance ◽  
Nmr Data ◽  
Protein Datasets

The success in backbone resonance sequential assignment is fundamental to three dimensional protein structure determination via Nuclear Magnetic Resonance (NMR) spectroscopy. Such a sequential assignment can roughly be partitioned into three separate steps: grouping resonance peaks in multiple spectra into spin systems, chaining the resultant spin systems into strings, and assigning these strings to non-overlapping consecutive amino acid residues in the target protein. Separately dealing with these three steps has been adopted in many existing assignment programs, and it works well on protein NMR data with close-to-ideal quality, while only moderately or even poorly on most real protein datasets, where noises as well as data degeneracies occur frequently. We propose in this work to partition the sequential assignment not by physical steps, but only virtual steps, and use their outputs to cross validate each other. The novelty lies in the places, where the ambiguities at the grouping step will be resolved in finding the highly confident strings at the chaining step, and the ambiguities at the chaining step will be resolved by examining the mappings of strings at the assignment step. In this way, all ambiguities at the sequential assignment will be resolved globally and optimally. The resultant assignment program is called Graph-based Approach for Sequential Assignment (GASA), which has been compared to several recent similar developments including PACES, RANDOM, MARS, and RIBRA. The performance comparisons with these works demonstrated that GASA is more promising for practical use.

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