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Finding Characteristic Substructures for Metabolite Classes

Authors: Marcus Ludwig, Franziska Hufsky, Samy Elshamy, and Sebastian Böcker

Published in: OASIcs, Volume 26, German Conference on Bioinformatics 2012


Abstract
We introduce a method for finding a characteristic substructure for a set of molecular structures. Different from common approaches, such as computing the maximum common subgraph, the resulting substructure does not have to be contained in its exact form in all input molecules. Our approach is part of the identification pipeline for unknown metabolites using fragmentation trees. Searching databases using fragmentation tree alignment results in hit lists containing compounds with large structural similarity to the unknown metabolite. The characteristic substructure of the molecules in the hit list may be a key structural element of the unknown compound and might be used as starting point for structure elucidation. We evaluate our method on different data sets and find that it retrieves essential substructures if the input lists are not too heterogeneous. We apply our method to predict structural elements for five unknown samples from Icelandic poppy.

Cite as

Marcus Ludwig, Franziska Hufsky, Samy Elshamy, and Sebastian Böcker. Finding Characteristic Substructures for Metabolite Classes. In German Conference on Bioinformatics 2012. Open Access Series in Informatics (OASIcs), Volume 26, pp. 23-38, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)


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@InProceedings{ludwig_et_al:OASIcs.GCB.2012.23,
  author =	{Ludwig, Marcus and Hufsky, Franziska and Elshamy, Samy and B\"{o}cker, Sebastian},
  title =	{{Finding Characteristic Substructures for Metabolite Classes}},
  booktitle =	{German Conference on Bioinformatics 2012},
  pages =	{23--38},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-44-6},
  ISSN =	{2190-6807},
  year =	{2012},
  volume =	{26},
  editor =	{B\"{o}cker, Sebastian and Hufsky, Franziska and Scheubert, Kerstin and Schleicher, Jana and Schuster, Stefan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.GCB.2012.23},
  URN =		{urn:nbn:de:0030-drops-37157},
  doi =		{10.4230/OASIcs.GCB.2012.23},
  annote =	{Keywords: metabolites, substructure prediction, mass spectrometry, FT-BLAST}
}
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