There are several computational tools available that can assist in predicting potential enzyme-metabolite pairings and their catalytic activities. One commonly used approach is molecular docking, which involves predicting the binding affinity and orientation of a metabolite within the active site of an enzyme. Tools like AutoDock, SwissDock, and DOCK are popular for performing such calculations. Additionally, machine learning algorithms trained on enzyme-metabolite interaction data can be used for prediction. Resources like EnzymeMiner and BRENDA offer comprehensive databases that can aid in identifying peroxidases and their potential substrates. However, it is important to note that these computational predictions are not always accurate, and experimental validation is crucial to confirm the catalytic activity of enzymes against specific metabolites.