Modeling Errors in NOE Data with a Log-normal Distribution Improves the Quality 
of NMR Structures

Rieping, W; Habeck, M; Nilges, M

doi:10.1021/ja055092c

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Modeling Errors in NOE Data with a Log-normal Distribution Improves the Quality of NMR Structures

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https://pubs.acs.org/doi/pdf/10.1021/ja055092c
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Rieping, W., Habeck, M., & Nilges, M. (2005). Modeling Errors in NOE Data with a Log-normal Distribution Improves the Quality of NMR Structures. Journal of the American Chemical Society, 127(46), 16026-16027. doi:10.1021/ja055092c.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-D385-4

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.