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Protein NMR structure determination with automated NOE-identification in the NOESY spectra using the new software ATNOS
Authors:Herrmann Torsten  Güntert Peter  Wüthrich Kurt
Affiliation:(1) Eidgenössische Technische Hochschule Zürich, Institut für Molekularbiologie und Biophysik, CH-8093 Zürich, Switzerland;(2) The Scripps Research Institute, 10550 N. Torrey Pines Rd., La Jolla, CA, 92037, U.S.A;(3) Present address: RIKEN Genomics Sciences Center, W505, 1-7-22 Suehiro, Tsurumi, Yokohama, 230-0045, Japan
Abstract:Novel algorithms are presented for automated NOESY peak picking and NOE signal identification in homonuclear 2D and heteronuclear-resolved 3D [1H,1H]-NOESY spectra during de novoprotein structure determination by NMR, which have been implemented in the new software ATNOS (automated NOESY peak picking). The input for ATNOS consists of the amino acid sequence of the protein, chemical shift lists from the sequence-specific resonance assignment, and one or several 2D or 3D NOESY spectra. In the present implementation, ATNOS performs multiple cycles of NOE peak identification in concert with automated NOE assignment with the software CANDID and protein structure calculation with the program DYANA. In the second and subsequent cycles, the intermediate protein structures are used as an additional guide for the interpretation of the NOESY spectra. By incorporating the analysis of the raw NMR data into the process of automated de novoprotein NMR structure determination, ATNOS enables direct feedback between the protein structure, the NOE assignments and the experimental NOESY spectra. The main elements of the algorithms for NOESY spectral analysis are techniques for local baseline correction and evaluation of local noise level amplitudes, automated determination of spectrum-specific threshold parameters, the use of symmetry relations, and the inclusion of the chemical shift information and the intermediate protein structures in the process of distinguishing between NOE peaks and artifacts. The ATNOS procedure has been validated with experimental NMR data sets of three proteins, for which high-quality NMR structures had previously been obtained by interactive interpretation of the NOESY spectra. The ATNOS-based structures coincide closely with those obtained with interactive peak picking. Overall, we present the algorithms used in this paper as a further important step towards objective and efficient de novoprotein structure determination by NMR.
Keywords:ATNOS  automated peak picking  CANDID  DYANA  nuclear magnetic resonance  nuclear Overhauser effect  protein structure determination
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