Practically, search of maximal common subgraph between two graphs is a NP-complete problem, which means the computational time increases exponentially when the molecular complexity increases. Therefore, to reduce computational cost, we set a timeout session of five seconds for each search of maximal common subgraph and discarded the failed search molecules for reaction prediction. We noticed approximately 20% of reaction prediction tasks were terminated due to the timeout. This is because the bio-active molecules which participate in the metabolic reactions cover a great range of molecular sizes. The timeout rate is also highly dependent on the MCS algorithm and hardware. Practically, the MCS was conducted We also noticed that SIMCOMP compares similarity of molecules mainly from their twodimensional features and, therefore, higher order structure differences in molecules (isotopes, stereoisomers, etc.) are hard to differentiate by applying SIMCOMP method, whilst enzymatic reactions are stereoisomer specific in most cases. However, this stereoisomer uncertainty could be avoided by applying the enzyme pairing algorithm below -a trained transformer model would learn the stereoisomer specificity from reaction SMILES, and pair with the corresponding enzyme structures, which would remove predicted reactions from infeasible stereoisomers.