(3bh) Understanding Nature's Catalysts: The Theoretical Description of Metallocluster Containing Enzymes

Metalloclusters are transition metal containing prosthetic groups found in all forms of life and facilitate some of the most remarkable chemistry on earth. For example, iron-sulfur containing enzymes are able to reduce atmospheric N₂ to ammonia at ambient conditions, as compared to Haber-Bosch process that is carried out at 400 C and 200 bar and which uses more than 1% of global energy production. As another example, nickel and molybdenum containing carbon monoxide dehydrogenase (CODH) can electrochemically convert CO₂ to CO with essentially no over-potential, whereas the best known synthetic catalysts, made of gold, are not only expensive but also require significant over-potential. Given the remarkable properties of metalloclusters, the detailed theoretical understanding of their action is clearly central not only to problems of biology, but also to inform new paradigms for designing materials for catalysis, energy, and beyond.

In my phd I studied the complex reaction mechanisms of soot formation and proposed pathways for formation of soot precursors using quantum chemical methods. My work demonstrated that it is possible to understand and even quantitatively predict the kinetics of highly complex, real-life systems, so long as reliable quantum chemical methods are available [C&F, 2010]. However, although commonly used quantum chemistry methods work well for the kinds of organic molecules that I had studied, they typically fail for metalloclusters, sometimes catastrophically, due to the strong electronic correlations in transition metal electronic structure.

Recently, with the advent of the Density Matrix Renormalization Group (DMRG) method, quantum chemistry now has a method that is in principle capable of treating the kinds of strongly correlated electronic structure found in metalloclusters. In my postdoctoral work I have made significant contributions to the development and application of the DMRG to the quantum chemical systems [ARPC, 2011]. To the best of my knowledge I have written the most efficient implementation of DMRG, which is furthermore capable of targeting specific spin states in molecules [JCP, 2012]. I have also demonstrated the power of the DMRG to model small molecules containing Fe_xS_y groups, which will be described in greater detail in the poster.

During my faculty appointment I intend to combine my expertise in advanced electronic structure methods and reaction dynamics to explore the thermochemistry and kinetics of realistic metallocluster containing enzymes. In particular, I will work to bridge the gap between the kinds of model problems that new electronic structure methods are developed for, and the challenges of describing kinetics in real materials and biological problems. This will require not only the applications of the current tools, but also development of new methodologies. A parallel direction will be to use our theoretical understanding of biological motifs to guide the design of synthetic metalloclusters for catalysis.