The number of subsystems required for MBE(n) grows as N n for a protein with N residues, and this combinatorial growth imposes a severe computational bottleneck, even for n = 3. In what follows, we screen the dimers and trimers based on distance, removing them from the calculation if the minimum interatomic distance between any two fragments exceeds a specified threshold, R cut . We then recompute E a and ∆ rxn E for COMT, with the caveat that we are careful to ensure that the same residues are included in the reactant, product, and transition state models. Tests of a distance-screened MBE(3) approximation (Fig. ) demonstrate that the predicted value of E a for COMT changes by < 0.1 kcal/mol as R cut is reduced from 25 Å to 8 Å. Setting R cut = 8 Å reduces the number of subsystems from 7,175 to 1,499 (as shown in Fig. ), yet has negligible effect on accuracy. Setting R cut = 8 Å, the computational effort is reduced from 2,025 h (which is the value shown in Fig. ) to 657 h. This figure is still 5× greater than the cost of the corresponding supersystem calculation, however. We include diffuse functions in our next set of tests (ωB97X-D/def2-SVPD), because a method that is intended for general application to enzymatic thermochemistry must be able to accommodate diffuse functions, in order to describe anionic side chains, yet these can be quite problematic for self-consistent charge schemes. Even if electrostatic embedding charges are fixed (say, from a force field), the use of diffuse functions can lead to overpolarization of the QM system by the MM charges. Errors in E a for COMT, computed using MBE(2) and MBE(3) approximations, are provided in Table . This includes results both with and without a HF/6-31G supersystem correction, and also with and without distance-based screening using R cut = 8 Å. We have also tabulated errors with respect to a ωB97X-D/ def2-TZVP calculation, which provides a measure of the basis-set incompleteness error when the smaller def2-SVPD basis set is used.