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Many of the current and future challenges that chemistry hopes to address require molecules of ever-increasing complexity.  We are synthetic inorganic chemists guided not only by the structural and functional sophistication of metalloenzymes, but also by the way Nature uses the process of evolution to arrive at these molecules. We leverage the versatility of sequence-defined oligomers to build and evolve macromolecular inorganic complexes that function as efficient catalysts and molecular machines for energy conversion and drug delivery.

Porous Peptidic Frameworks
Porous materials have many uses including molecular separations, catalysis, and drug delivery. As peptides are extremely modular building blocks, using them to create porous frameworks can lead to materials that have highly complex and dynamic pores resembling protein active sites, which could be varied and evolved for a number of applications. Our group develops reliable strategies to design and synthesize porous materials from peptides, and we are working to understand fundamental sequence-structure relationships, as well as, develop useful applications.

Evolvable Catalysts

Homogeneous metal complexes have proven to be powerful catalysts for numerous applications ranging from small-molecule transformation to organic synthesis.  However, slight inaccuracies in "rational" design of catalysts can manifest as drastic reduction in catalysis rate and selectivity. We propose that applying the process of evolution to synthetic systems can lead to highly effective catalyst generation. Sequence-defined oligomers are ideal candidates to build such catalysts due to their modular and efficient assembly, while their sequence-defined nature facilitates the process of variation and selection.

Multimetallic Chemistry

Multimetallic clusters are present in enzymes that perform remarkable small-molecule transformations, including carbon dioxide reduction, methane oxidation, and water oxidation. We are targeting macromolecular ligands to assemble cluster complexes that represent simplified yet accurate models of multimetallic enzyme active sites.

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