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TSAR: a program for automatic resonance assignment using 2D cross-sections of high dimensionality, high-resolution spectra

Journal article
Authors Anna Zawadzka-Kazimierczuk
Wiktor Kozminski
Martin Billeter
Published in Journal of Biomolecular NMR
Volume 54
Issue 1
Pages 81-95
ISSN 0925-2738
Publication year 2012
Published at Department of Chemistry and Molecular Biology
Pages 81-95
Language en
Keywords Algorithm Automated resonance assignment, High-dimensional fast NMR, Intrinsically disordered protein
Subject categories Structural Biology, Molecular biophysics


While NMR studies of proteins typically aim at structure, dynamics or interactions, resonance assignments represent in almost all cases the initial step of the analysis. With increasing complexity of the NMR spectra, for example due to decreasing extent of ordered structure, this task often becomes both difficult and time-consuming, and the recording of high-dimensional data with high-resolution may be essential. Random sampling of the evolution time space, combined with sparse multidimensional Fourier transform (SMFT), allows for efficient recording of very high dimensional spectra (≥4 dimensions) while maintaining high resolution. However, the nature of this data demands for automation of the assignment process. Here we present the program TSAR (Tool for SMFT-based Assignment of Resonances), which exploits all advantages of SMFT input. Moreover, its flexibility allows to process data from any type of experiments that provide sequential connectivities. The algorithm was tested on several protein samples, including a disordered 81-residue fragment of the δ subunit of RNA polymerase from Bacillus subtilis containing various repetitive sequences. For our test examples, TSAR achieves a high percentage of assigned residues without any erroneous assignments.

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