Exploiting image registration for automated resonance assignment in NMR

Madeleine Strickland, Thomas Stephens, Jian Liu, Nico Tjandra

Research output: Contribution to journalArticle

Abstract

Analysis of protein NMR data involves the assignment of resonance peaks in a number of multidimensional data sets. To establish resonance assignment a three-dimensional search is used to match a pair of common variables, such as chemical shifts of the same spin system, in different NMR spectra. We show that by displaying the variables to be compared in two-dimensional plots the process can be simplified. Moreover, by utilizing a fast Fourier transform cross-correlation algorithm, more common to the field of image registration or pattern matching, we can automate this process. Here, we use sequential NMR backbone assignment as an example to show that the combination of correlation plots and segmented pattern matching establishes fast backbone assignment in fifteen proteins of varying sizes. For example, the 265-residue RalBP1 protein was 95.4 % correctly assigned in 10 s. The same concept can be applied to any multidimensional NMR data set where analysis comprises the comparison of two variables. This modular and robust approach offers high efficiency with excellent computational scalability and could be easily incorporated into existing assignment software.

Original languageEnglish (US)
Pages (from-to)143-156
Number of pages14
JournalJournal of Biomolecular NMR
Volume62
Issue number2
DOIs
StatePublished - Jun 4 2015
Externally publishedYes

Keywords

  • Automation
  • Backbone assignment
  • Cross-correlation
  • FFT
  • Fast Fourier transform

ASJC Scopus subject areas

  • Biochemistry
  • Spectroscopy

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