title: Modeling errors in NOE data with a log-normal distribution improves the quality of NMR structures.
abstract: The distribution of the deviation of calculated from measured nuclear Overhauser effect (NOE) intensities is a priori unknown. The use of a log-normal distribution to describe these deviations permits the direct calculation of a structure from the measured intensities without first converting them into distance bounds. We show that the log-normal distribution is a natural choice for describing errors in NOE data and that it improves the accuracy, precision, and quality of the calculated structures compared to the usual bounds representation.
authors.affiliation: Unité de Bioinformatique Structurale, CNRS URA 2185, Institut Pasteur, 25-28 rue du docteur Roux, F-75015 Paris, France.
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Rieping
authors.forename: Michael
authors.initials: M
authors.lastname: Habeck
authors.forename: Michael
authors.initials: M
authors.lastname: Nilges
mesh_terms: D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D008956:Models, Chemical