TY - JOUR
T1 - Automated protein NMR structure determination using wavelet de-noised NOESY spectra
AU - Dancea, Felician
AU - Günther, Ulrich
N1 - Funding Information:
This work was supported by the Large Scale Facility Frankfurt (UNIFRANMR) and by the RTD project FIND from the European Community.
Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2005/11
Y1 - 2005/11
N2 - A major time-consuming step of protein NMR structure determination is the generation of reliable NOESY cross peak lists which usually requires a significant amount of manual interaction. Here we present a new algorithm for automated peak picking involving wavelet de-noised NOESY spectra in a process where the identification of peaks is coupled to automated structure determination. The core of this method is the generation of incremental peak lists by applying different wavelet de-noising procedures which yield peak lists of a different noise content. In combination with additional filters which probe the consistency of the peak lists, good convergence of the NOESY-based automated structure determination could be achieved. These algorithms were implemented in the context of the ARIA software for automated NOE assignment and structure determination and were validated for a polysulfide-sulfur transferase protein of known structure. The procedures presented here should be commonly applicable for efficient protein NMR structure determination and automated NMR peak picking.
AB - A major time-consuming step of protein NMR structure determination is the generation of reliable NOESY cross peak lists which usually requires a significant amount of manual interaction. Here we present a new algorithm for automated peak picking involving wavelet de-noised NOESY spectra in a process where the identification of peaks is coupled to automated structure determination. The core of this method is the generation of incremental peak lists by applying different wavelet de-noising procedures which yield peak lists of a different noise content. In combination with additional filters which probe the consistency of the peak lists, good convergence of the NOESY-based automated structure determination could be achieved. These algorithms were implemented in the context of the ARIA software for automated NOE assignment and structure determination and were validated for a polysulfide-sulfur transferase protein of known structure. The procedures presented here should be commonly applicable for efficient protein NMR structure determination and automated NMR peak picking.
UR - http://www.scopus.com/inward/record.url?scp=31444443329&partnerID=8YFLogxK
U2 - 10.1007/s10858-005-3093-1
DO - 10.1007/s10858-005-3093-1
M3 - Journal articles
C2 - 16331419
AN - SCOPUS:31444443329
SN - 0925-2738
VL - 33
SP - 139
EP - 152
JO - Journal of Biomolecular NMR
JF - Journal of Biomolecular NMR
IS - 3
ER -