Computational Methods In Organometallic Catalysis PDF Download

"Presently, most industrial chemical production relies on catalytic processes, that represent an economical and more environmentally friendly alternative to classic stoichiometric methodologies. The use of organometallic catalysts enables many difficult chemical transformations due to the ability of transition metals to activate organic molecules. However, even catalytic amounts of metals remain a major environmental issue. The beginning of the 21st century was marked by the establishment of biocatalysis in industry as green alternative to metallo- and organometallic catalysis. Biocatalysts are fascinating bio-machines characterized by high selectivity, biodegradability and operation under mild, environmentally friendly conditions. The vast majority of biocatalysts are enzymes, proteins that have a catalytic function. One reason for the rapid progress in this field is the increasing use of computational tools in protein engineering and the ever-growing structural information available. This thesis describes a series of studies of organometallic (bio)-catalysts using several computational techniques. The goals have been to gain a deeper understanding of the range of capabilities of the (bio)-catalysts studied, and to develop new tools that can be helpful in medicinal chemistry and in biocatalysis projects.First, a review of biocatalysts and organometallic (bio)-catalysts is presented from the point of view of computational chemistry. Next, a mechanistic study of a ruthenium catalyzed coupling reaction is described: using DFT, a number of potential pathways are evaluated and a complex catalytic cycle is elucidated. In practice, such detailed investigations can only be done for a selected number of molecules and with metal complexes of limited size. While the ruthenium catalyst was modeled without truncation, using DFT on the entire active site of an enzyme is not an option. Molecular properties and descriptors that are fast to compute can replace lengthy calculations, albeit with reduced accuracy. In the study of the catalytic complex of Cytochrome P450s metabolizing enzymes described next, a truncated version of the oxo-iron heme complex is used. A detailed DFT study of an aromatic oxidation reaction catalyzed by this complex is presented and a method to predict the product drug oxidation using Frontier Molecular Orbital theory is outlined. The use of local reactivity descriptors was then probed as a way to further increase the accuracy of sites of oxidation prediction. However, reactivity of substrates is not the only property that influences the selectivity of oxidation. The structure of the active site plays an important role as well. With smaller systems such as the ruthenium complex, several conformations can be generated and examined. This approach is inappropriate for larger systems such as enzymes. To study how the structure of the catalytic site impacts the selectivity of Cytochrome P450s, a method for virtual mutagenesis was developed. Structural changes induced by mutations were modeled using Normal Mode Analysis and a rotamer library toolkit (previously reported). The potential of the programs developed for virtual biocatalysis design was demonstrated using a case study on Cytochrome P450s metabolic project." --