Convergence of electronic structure calculations on systematically larger enzyme models is slow, requiring 300-600 atoms or more before the result no longer changes with respect to the inclusion of additional amino acids in the quantum mechanical (QM) model region. This is true whether the quantity of interest is a barrier height or a reaction energy, or whether it is the interaction energy for non-covalent binding of a ligand to a protein. In view of this, the current state-of-theart for modeling enzymatic active sites or ligand binding sites using quantum chemistry relies on bespoke or "artisanal" QM models, constructed to purpose by hand, without well-defined criteria to guide the process. Slowly this is beginning to change, as tools for automated QM model selection are developed. In the present work, we evaluate the use of such procedures for obtaining energetically converged molecular models of ligand binding sites in enzymes. Our strategies combines a semi-empirical quantum chemistry model with a fragment-based procedure for computing the interaction energy (∆E int ) between a ligand and an enzyme model. The latter is constructed in an automated way, and this facilitates high-throughput investigation of a large number of enzyme models at low cost. Given an appropriate model, one can then apply convergent, fragment-based protocols to evaluate ∆E int at higher lev- * herbert@chemistry.ohio-state.edu els of theory. That might be density functional theory (DFT), although the fragments are small enough that the use of correlated wave function models is also feasible.