We propose a graph method to predict biological reactions to explore the biochemical reactions domain. The method is target molecule-oriented, i.e. for a target molecule of interests 𝑡, based on the existing enzymatic transformations in biological reactions, to predict novel reactions from the existing similar functional groups. The diversified reaction space would combine literature-excerpted reactions from the database and calibrated predicted reactions for all target molecules. The workflow of the proposed method is shown in Figure . similar molecule 𝑠 " is determined by Eq. 3, which is the ratio between the intersection set and the union set of the molecular graphs. The above steps were implemented via a Python script to interact with SIMCOMP API. The full list of similar compounds for all KEGG molecules can be found in Section S2 of ESI.