Multiscale modeling of (bio) catalytic systems

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The modeling of complex systems in chemistry, physics, biology, materials science and related interdisciplines has taken great strides in recent years. In the areas of interest to this proposal, advances in quantum chemistry, in molecular mechanics and molecular dynamics, in statistical and stochastic methodologies and in the treatment of kinetic networks are merging. And an embryonic systems approach is emerging. Some of the most interesting frontier work is interdisciplinary and integrative in nature and requires theories and methodologies that span large ranges on spatial and temporal scales. The long-term goal of my research program is to contribute to the development of such multi-scale modeling methodologies, to their implementation in efficient computer codes, and their application to catalytically-driven processes in complex biological and energy-related environments. Success would lead to better understanding of biological systems, of how biochemical reactions are coupled to larger scale properties of cellular components and of how they work together. In the area of electron-transfer between proteins, we have successfully elucidated the role of water in modulating the electron transfer between the proteins MADH and Amicyanin. We have developed a methodology to compute the effects of quantum decoherence on the rates. In the upcoming grant cycle we will extend this work to other examples of protein pairs and also work on methodology to remove the empirical aspects of the tunneling pathway approach. We will start a new project on proton transfers in the respiratory chain, which will require methodology for nuclear quantum effects and extend the project to proton-coupled electron transfers. We have explored the reaction network for biological transcription and translation using empirical rate constants. Quantum Mechanical/Molecular Mechanical (QM/MM) simulations have been carried out for various steps in the formation of m-RNA by RNA Polymerase. Conformational changes have been identified and the chemical reaction has been mapped out using a rapid semi-empirical quantum mechanical method. The project will be extended to important mutants and also the effects on RNA reactions of substituting the catalytically important Mg ions by other metals, starting with Fe. The methods can also be used to understand petroleum chemistry under realistic conditions, such as those in heavy oil deposits or in the oil sands. New ultradispersed catalysts will be designed by a combined computational-experimental (in collaboration with Pereira's group) approach so that some of the important chemistry can be done underground, with less impact on the environment. So far, we have explored the potential energy surface for the hydrogenation of benzene as a model molecule using Density Functional Theory with both periodic and cluster models. Simulations and benchmarking of two rapid semiempirical methods (DFTB and TBQCMD) are ongoing. Preliminary DFTB simulations on a model including hydrocarbon, nanocatalyst and a silica (sand) model have shown that a Mo2C nanoparticle can dissociate hydrogen and crack hexadecane. Extensions to hydrogenation and cracking of polyaromatic hydrocarbons are planned. Calculations of the free energy profiles for selected reactions will be carried out with QM/MM methodology using DFTB/CHARMM and umbrella sampling. As a high-risk, speculative, element of my research program (10-15% effort) I am collaborating with Stuart Kauffman and Gabor Vattay on using the eigenvalue spectra of molecules to situate them in the "poised realm" which has axes, X going from ordered to critical to chaotic and Y measuring the extent of quantum decoherence. Preliminary results show that biological molecules tend to be critical.