Metabolic Pathway Predictions for Metabolomics: A Molecular Structure Matching Approach

نویسندگان

  • Mai Hamdalla
  • Sanguthevar Rajasekaran
  • David F. Grant
  • Ion I. Mandoiu
چکیده

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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عنوان ژورنال:
  • Journal of chemical information and modeling

دوره 55 3  شماره 

صفحات  -

تاریخ انتشار 2015