UCLA

The development of catalysts for faster, more selective, and more sustainable chemical reactions remains an outstanding goal in chemistry. While advancements in statistical models have greatly improved our predictive ability, physical models remain our most valuable tools for mechanistic understanding. Density functional theory (DFT) calculations provide structural models of reaction intermediates and transition states and can accurately predict thermodynamic quantities. For larger systems, molecular dynamics (MD) simulations using classical force fields model time-dependent movements of protein-ligand complexes. This Thesis combines both approaches to model several designed and engineered catalysts.In Chapter 2, we investigate dirhodium catalysts that were designed to catalyze an enantioselective Si–H insertion. Our experimental collaborators observed that the enantioselectivity of the reaction correlated strongly with the Hammet constant of the carbene’s aryl substituents but lacked a clear understanding as to why. DFT calculations using an Rh2(OAc)4 catalyst showed that the aryl rings of the carbene rotate in the transition state, resulting in one aryl conjugating with the vacant carbene p-orbital. For asymmetrically substituted carbenes, the transition state with the electron-rich aryl conjugated to the vacant carbene p-orbital was always lower in energy, and this energy difference increased with greater electronic differences between the rings. We then showed that because of this geometric constraint, the chiral environment of the designed catalysts favored one enantiomeric transition state over the other. Again, the energy difference between transition states correlated with the differences in Hammet substituent constants between the rings. In Chapter 3, we investigate a laboratory-evolved family of flavin-dependent halogenases with orthogonal selectivity for the chlorination of tryptamine. Few mutations separate the wild type from the most distant mutant, and crystal structures show that there are minimal structural differences between the enzymes. DFT calculations and MD simulations established that a catalytic lysine activates HOCl through general acid catalysis for chlorination of the substrate. Energetic differences in the transition states or Wheland intermediates calculated by DFT showed the intrinsic site selectivity for each substrate. Docking calculations and MD simulations of protein-substrate complexes showed how each enzyme binds the substrate to position a single site closest to the halogenating species, influencing the site selectivity of this reaction. Our physical model was then used to predict site selectivity for several nonnative substrates. Finally, Chapter 4 investigates a set of computationally designed enzymes with varying activity for a chemiluminescence reaction. Initial designs were optimized by site-saturation mutagenesis, and it was not clear why the final proteins were so much more active than the initial designs. Our DFT calculations confirmed the proposed reaction mechanism and showed that anion formation in the substrate was critical for the reaction. Docking calculations and MD simulations showed that LuxSit-i, the most active variant, was the best at stabilizing this anion in the transition states. Changing the substituent resulted in worse stabilization during the simulations, which is consistent with the observed substrate specificity. All three of these chapters explore notable examples of catalyst engineering and provide physical models for their mechanisms. The insight gained here will hopefully lead to future generations of engineered catalysts with continuously improved capabilities.