In Silico Atom Labeling for the Reconstruction of Atom-mapped Metabolic Networks

Field of atom mapping of metabolic networks is lacking an automated approach, which accounts for the information of reaction mechanism for atom mapping and is extendable from atom-mapped reactions to atom-mapped reaction networks. We developed “iAM.NICE” (in silico Atom Mapped Network Integrated Computational Explorer), for the atom-level reconstruction of metabolic networks from the in silico labeled substrates to elucidate the mass flow in a biochemical reaction network. “iAM.NICE” transfers the label(s) from a substrate to a product by taking into account the information about the rearrangements of the chemical bonds derived from the “generalized reaction rules” introduced in [1] . It uses the 582 reaction rules that cover the reconstruction of   90% of known enzymatic reactions (KEGG database). The originality of “iAM.NICE” stems from two aspects: the first automated atom-mapping algorithm that is derived from the underlying enzymatic biotransformation mechanism. its application is not limited to individual reactions and it can be used for the reconstruction of atom-mapped metabolic networks.


    • EPFL-POSTER-210974

    Record created on 2015-09-04, modified on 2017-05-12


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