We demonstrate the method by using it to rediscover tertiary amines and phosphines as catalysts for the MBH reaction. Building reaction networks for 11 possible catalysts candidates representing different functional groups (amines, phosphines, sulfides, alkenes, acids, bases and carbonyl groups), tertiary amines and phosphines clearly stand out as the most promising catalyst candidates. Furthermore, the reaction networks are used to extract information about possible side reactions; in this case we identified no relevant sidereactions that are competitive with the desired catalytic mechanism. The tertiary amine template, TMA, identified by the screening of possible catalyst candidates is used as a starting point for the GA proposed by Seumer et al. and found that the optimized catalyst candidates performed similarly to the experimentally validated M10 catalyst suggested by Seumer et al. at the B3LYP/6-31+G(d,p) level of theory with methanol modelled as a continuum solvent using the SMD model. A method for catalyst candidate identification requires that screening of possible candidates is practically possible, meaning that growing the reaction networks must be fast. We achieve this by focusing on screening intermediate Gibbs free energies rather than searching for TSs. Furthermore, the meta-MD simulations are performed at the fast semi-empirical level of theory GFN2-xTB. The combination of this method for catalyst candidate discovery with the GA-based catalyst optimization method by Seumer et al. results in an algorithm for truly de novo catalyst discovery.