We present steps toward the construction of a quantum-chemical benchmark set for enzymatically catalyzed reactions comprising different-quite sizable-model systems for five reactions. Our work is inspired by a study of semiempirical molecular-orbital theory methods against B3LYP-based structures and energies [ Kromann et al. PeerJ 2016 , 4 , e1994 ]. Taking the same model systems, we herein demonstrate first how adequate treatments of London dispersion and basis-set superposition error lead to structural differences compared to structures obtained at the popular B3LYP/6-31G(d,p) level. The changes observed by us have a significant influence on the final reaction barrier heights (BHs) and energies (REs), which are our main focus herein. We then proceed and carefully investigate different strategies to obtain either exact or estimated complete-basis-set BHs and REs with the help of the DLPNO-CCSD(T) approach, which offers an exciting path into exploring larger biochemically relevant structures at the coupled cluster level. On the basis of our analysis, we present three strategies for obtaining reliable values. While these recommendations constitute our main findings and are meant to be used as useful guidelines for others in the field, we demonstrate their applicability in a preliminary benchmark set comprising 16 BHs and 12 REs on which we assess 35 density functional theory (DFT) approximations. This preliminary benchmark study was used as an indicator for the validity of our approach toward generating such a benchmark set, based on the fact that we were able to reproduce major recommendations in the field of modern DFT, such as the reproduction of the famous Jacob's Ladder scheme, while also pointing out subtle differences to previous benchmark studies. We end our study by critically assessing the still popular choice to gauge the accuracy of low-level methods against B3LYP data, and we show the risks of such a strategy, adding to the ever-growing list of calls to move away from B3LYP as a standard black-box approach.