4.7 Article

Metabolic Pathway Predictions for Metabolomics: A Molecular Structure Matching Approach

Journal

JOURNAL OF CHEMICAL INFORMATION AND MODELING
Volume 55, Issue 3, Pages 709-718

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/ci500517v

Keywords

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Funding

  1. NIH [1R01GM087714]
  2. Agriculture and Food Research Initiative Competitive from the USDA National Institute of Food and Agriculture [2011-67016-30331]
  3. NSF [IIS-0916948]
  4. Booth Engineering Center for Advance Technology (BECAT) at the University of Connecticut

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Metabolic pathways are composed of a series of chemical reactions occurring within a cell. In each pathway, enzymes catalyze the conversion of substrates into structurally similar products. Thus, structural similarity provides a potential means for mapping newly identified biochemical compounds to known metabolic pathways. In this paper, we present TrackSM, a cheminformatics tool designed to associate a chemical compound to a known metabolic pathway based on molecular structure matching techniques. Validation experiments show that TrackSM is capable of associating 93% of tested structures to their correct KEGG pathway class and 88% to their correct individual KEGG pathway. This suggests that TrackSM may be a valuable tool to aid in associating previously unknown small molecules to known biochemical pathways and improve our ability to link metabolomics, proteomic, and genomic data sets. TrackSM is freely available at http://metabolomics.pharm.uconn.edu/?q=Software.html.

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