Enzymes are attractive catalysts for organic synthesis because they function under mild reaction conditions and can provide a high degree of stereoselectivity. Despite these advantages, the use of enzymes for chemical synthesis is limited by the scope of reactions available in nature. Introduction of non-natural metal complexes into proteins is one strategy to increase the diversity of chemical reactions available. A challenge with this approach is finding a protein that can accommodate the metal complex. To address this challenge, a computational method was developed to rapidly search the entire Protein Data Bank (PDB) for protein structures that possess a cavity large enough to harbor a particular metal catalyst. As a proof of principle, this computational analysis was used to identify proteins capable of supporting the metal-binding ligand 1,10-phenanthroline. From this computational search, five proteins were found. Cysteines were introduced in specific locations within the cavities of these proteins to allow for immobilization of the metal complex, and the genes were cloned into an expression vector. Following protein expression and purification, a copper-phenanthroline complex was introduced. The activity of these artificial metalloenzymes was then characterized in a model Friedel-Crafts alkylation reaction. This work promises to expand the use of artificial metalloenzymes in chemical synthesis by enabling more facile selection of protein scaffolds for a variety of metal catalysts.

Computational identification of protein scaffolds for the generation of artificial metalloenzymes

2019 Spring National Meeting

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