Authors: Julia M Würz Peter Güntert
Publish Date: 2017/02/03
Volume: 67, Issue: 1, Pages: 63-76
Abstract
The automated identification of signals in multidimensional NMR spectra is a challenging task complicated by signal overlap noise and spectral artifacts for which no universally accepted method is available Here we present a new peak picking algorithm CYPICK that follows as far as possible the manual approach taken by a spectroscopist who analyzes peak patterns in contour plots of the spectrum but is fully automated Human visual inspection is replaced by the evaluation of geometric criteria applied to contour lines such as local extremality approximate circularity after appropriate scaling of the spectrum axes and convexity The performance of CYPICK was evaluated for a variety of spectra from different proteins by systematic comparison with peak lists obtained by other manual or automated peak picking methods as well as by analyzing the results of automated chemical shift assignment and structure calculation based on input peak lists from CYPICK The results show that CYPICK yielded peak lists that compare in most cases favorably to those obtained by other automated peak pickers with respect to the criteria of finding a maximal number of real signals a minimal number of artifact peaks and maximal correctness of the chemical shift assignments and the threedimensional structure obtained by fully automated assignment and structure calculationWe thank Torsten Herrmann for providing NOESY spectra and peak lists produced by ATNOS for the CASDNMR proteins Piotr Klukowski for providing peak lists produced by the CVPeak Picker software and Fred Damberger for helpful discussions We gratefully acknowledge financial support by the Lichtenberg program of the Volkswagen Foundation a GrantinAid for Scientific Research of the Japan Society for the Promotion of Science JSPS and a Eurostars grant by the Swiss Confederation
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