Qiang Cui of the University of Wisconsin is supported by the Chemical Theory, Models and Computational Methods program in the Chemistry Division to develop novel computational methods such that enzyme catalysis in complex environments can be effectively analyzed with theoretical techniques. The first development targets chemical reactions that involve ligands of complex metal clusters in enzymes. Cui and coworkers are developing a novel quantum mechanical/molecular mechanical (QM/MM) framework in which only the reactive ligand and other groups that explicitly participate the chemistry are treated with QM, while the rest of the metal motif is treated at a MM level with an advanced valence-bond force field. Variations in the interaction between the QM ligand and the MM metal motif during the reaction are treated with a chemical potential equalization approach, which avoids technical complications associated with explicitly treating the QM region as an open system. The second subject concerns the development of mixed-resolution simulations. This development takes advantage of a coarse-grained (CG) model established in the Cui group for water, lipids and amino acids that features a careful treatment of electrostatics. For the calibration of atomistic/CG interactions, in addition to the common strategy of using all-atom simulations as a reference, the unique aspect of this approach is to also take advantage of experimental thermodynamic data for multi-component solutions.
These developments meet the computational and theoretical challenges associated with understanding how enzymes catalyze chemical reactions. By avoiding the explicit treatment of the complex electronic structure of metal clusters, the novel QM/MM framework allows computational chemists and biologists to study chemical reactions in complex systems of biological relevance. It is particularly powerful for modeling interesting and important complex processes such as the proton-coupled-electron-transfers that occur in photosynthesis. The mixed atomistic/CG approach is demanded in many applications that require a high-resolution description of the protein and a realistic description of the complex environment, such as a multi-component lipid bilayer with specific curvature. These methods find applications in broad areas that go beyond physical chemistry to include enzymology, biophysics/biochemistry and bio-inorganic chemistry. Development of mixed-resolution models greatly expand the scale and complexity of systems that can be meaningfully treated with computations, and thus impact materials science and cellular biochemistry. The computational methods developed in this project are implemented into the popular molecular simulation package, CHARMM, and can be used to study a broad range of problems in chemistry and biology. The outreach component of the project helps emphasize the role of theoretical and computational chemistry in understanding nature and stimulate young students to pursue careers in science.
