Modeling Metalloenzymes with Density Functional and Mixed Quantum Mechanical/Molecular Mechanical (QM/MM) Calculations: Progress and Challenges

Abstract

AbstractWe discuss the application of density functional theory (DFT)‐based quantum chemical and mixed quantum mechanics/molecular mechanics (QM/MM) methods to the modeling of metalloenzyme chemistry. The state of the art of current approaches in terms of accuracy and reliability is considered, primarily in the context of two example systems, methane monooxygenase (MMO) and cytochrome P450. Key issues include the intrinsic accuracy of current DFT functionals for metal‐containing systems, modeling of conformational changes in protein structure, treatment of environmental electrostatic effects, use of spectroscopic calculations to help in identifying the structures of intermediates, and the validity of standard transition state theory approximations using a small number of optimized structures, as opposed to performing full statistical mechanical sampling with methods such as free energy perturbation theory. Considerable insight into the catalytic cycles of both MMO and P450 have been obtained over the past decade using existing computational methods, in close coupling with experimental efforts. However, significant challenges remain, both for the two systems that we consider here and for the modeling of metalloenzyme chemistry in the general case. A number of the most important of these challenges are identified and prospects for addressing them via improvements of the theoretical methodology are discussed.