  Computational prediction of enzyme mechanism and protein function requires
accurate physics-based models and suitable sampling. We discuss recent advances
in large-scale quantum mechanical (QM) modeling of biochemical systems that
have reduced the cost of high-accuracy models. Trade-offs between sampling and
accuracy have motivated modeling with molecular mechanics (MM) in a multi-scale
QM/MM or iterative approach. Limitations to both conventional density
functional theory (DFT) and classical MM force fields remain for describing
non-covalent interactions in comparison to experiment or wavefunction theory.
Because predictions of enzyme action (i.e., electrostatics), free energy
barriers, and mechanisms are sensitive to the protocol and embedding method in
QM/MM, convergence tests and systematic methods for quantifying QM-level
interactions are a needed, active area of development.
