Abstract
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.
| Originalsprache | Englisch |
|---|---|
| Zeitschrift | Journal of Biomolecular NMR |
| Jahrgang | 33 |
| Ausgabenummer | 3 |
| Seiten (von - bis) | 139-152 |
| Seitenumfang | 14 |
| ISSN | 0925-2738 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - 11.2005 |
Fördermittel
This work was supported by the Large Scale Facility Frankfurt (UNIFRANMR) and by the RTD project FIND from the European Community.
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Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung
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Strategische Forschungsbereiche und Zentren
- Forschungsschwerpunkt: Infektion und Entzündung - Zentrum für Infektions- und Entzündungsforschung Lübeck (ZIEL)
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