ARIA: automated NOE assignment and NMR structure calculation
In the light of several ongoing structural genomics projects, faster and more reliable methods for structure calculation from NMR data are in great demand. The major bottleneck in the determination of solution NMR structures is the assignment of NOE peaks (nuclear Overhauser effect). Due to the high...
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Published in | Bioinformatics (Oxford, England) Vol. 19; no. 2; pp. 315 - 316 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Oxford
Oxford University Press
22.01.2003
Oxford Publishing Limited (England) |
Subjects | |
Online Access | Get full text |
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Summary: | In the light of several ongoing structural genomics projects, faster and more reliable methods for structure calculation from NMR data are in great demand. The major bottleneck in the determination of solution NMR structures is the assignment of NOE peaks (nuclear Overhauser effect). Due to the high complexity of the assignment problem, most NOEs cannot be directly converted into unambiguous inter-proton distance restraints.
We present version 1.2 of our program ARIA (Ambiguous Restraints for Iterative Assignment) for automated assignment of NOE data and NMR structure calculation. We summarize recent progress in correcting for spin diffusion with a relaxation matrix approach, representing non-bonded interactions in the force field and refining final structures in explicit solvent. We also discuss book-keeping, data exchange with spectra assignment programs and deposition of the analysed experimental data to the databases.
ARIA 1.2 is available from: http://www.pasteur.fr/recherche/unites/Binfs/aria/.
XML DTDs (for chemical shifts and NOE crosspeaks), Python scripts for the conversion of various NMR data formats and the results of example calculations using data from the S. cerevisiae HRDC domain are available from: http://www.pasteur.fr/recherche/unites/Binfs/aria/ |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1367-4803 1367-4811 |
DOI: | 10.1093/bioinformatics/19.2.315 |