Pathway View: Map PDB Data onto Metabolic Pathways Select an organism and a metabolic pathway from the pulldown menus to view a map. Organism Please select ... Map Please select ... Legend for Reaction Data   No data   Only homology models   PDB entries & homology models Show Full Names Export SVG Export PNG Legend for Metabolite Data   No data   PDB ligands available An example map is shown below: In a reaction pathway map, each arrow represents a reaction and each node represents a metabolite. The size and color of each reaction arrow indicates the number of PDB entries or homology models that are associated with it. If there is no PDB entry associated with a reaction, its arrow will be gray. If there are only homology models associated with a reaction, its arrow will be yellow. If there are PDB entries associated with a reaction, the color of its arrow will vary from light blue to dark blue depending on the number of associated entries in that map. The color of a metabolite node indicates the presence (blue) or absence (gray) of the compound in the wwPDB Chemical Component Dictionary (CCD). Clicking on a node or arrow will reveal the associated ligand ID or a list of the associated PDB entries, respectively. The last character of a metabolite may indicate its compartment : _c -> cytosolic _m -> mitochondrial _e -> extracellular space The lighter numbers displays the stoichiometry of the metabolite in the reaction. When it is 1, we hide the number. The PDB to Reaction mapping is based on the data provided by GEM-PRO project. In brief, genes are linked to proteins and proteins interact with metabolites. Therefore genes and proteins can be associated with reactions and metabolites in the provided genome-scale models. In order to associate a PDB id with a reaction, we use the relation from Gene to UniProt to PDB. (Gene -> UniProt -> PDB). The UniProt to PDB mapping is available from the SIFTS initiative. ESCHER BiGG The PDB to Reaction mapping is based on the data provided by GEM-PRO project. See also Brunk et al. BMC Systems Biology (2016).