Duplicate detection of 2D-NMR Spectra

Abstract

2D-Nuclear magnetic resonance (NMR) spectra are used in the (structural) analysis ofsmall molecules. In contrast to 1D-NMR spectra, 2D-NMR spectra correlate the chemicalshifts of1H and13C at the same time. A spectrum consists of several peaks in a two-dimensional space. The most important information of a peak is the location of its center,which captures the bonding relationships of hydrogen and carbon atoms. A spectrum con-tains much information about the chemical structure of a product, but in most cases thestructure cannot be read off in a simple and straightforward manner. Structure elucidationinvolves a considerable amount (manual) efforts.Using high-field NMR spectrometers, many 2D-NMR spectra can be recorded in shorttime. So the common situation is that a lab or company has a repository of 2D-NMRspectra, partially annotated with the structural information. For the remaining spectra thestructure in unknown. In case two research labs are collaborating, the repositories will bemerged and annotations shared.We reduce that problem to the task of finding duplicates in a given set of 2D-NMR spectra.Therefore, we propose a simple but robust definition of 2D-NMR duplicates, which allowsfor small measurement errors. We give a quadratic algorithm for the problem, which canbe implemented in SQL. Further, we analyze a more abstract class of heuristics, which arebased on selecting particular peaks. Such a heuristic works as a filter step on the pairs ofpossible duplicates and allows false positives. We compare all methods with respect totheir run time. Finally we discuss the effectiveness of the duplicate definition on real data.