Peptide driven synthesis of inorganic nanomaterials has received much attention due to the potential of creating materials with optimized/tunable properties through sequence manipulation. While there is a large amount of literature available on the fabrication of nanoparticles using peptides, comparatively little is known the nanomaterial’s in-depth atomic structure. Such information is an important prerequisite for rational sequence design which can result in nanomaterials with tunable properties. Using a hybrid experimental/computational approach, sequence-dependent structure/function relationships are assessed and predicted by combining X-ray characterization methods and molecular dynamics simulations for monometallic and bimetallic systems. First, extended X-ray absorption fine-structure spectroscopy (EXAFS) is performed on peptide-capped nanoparticles to determine sequence-dependence in local chemistry and structural disorder. From there, high-energy X-ray diffraction (HE-XRD) data was taken and coupled with atomic pair distribution function (PDF) analysis to obtain sub-atomic scale structural details over the entire nanoparticle structure. Reverse Monte Carlo simulations of the PDF data, which are guided by the EXAFS data and other constraints, are used to obtained nanoparticle configurations, which demonstrate sequence-dependent structural disorder. From there, molecular dynamics methods are used to relax particle structures, model peptide morphology on the experimentally-determined structures, and finally used to assess catalytic properties to provide sorely lacking sequence-dependent structure/function relationships. The aforementioned methodology presents a widely-applicable route for peptide-enabled systems to provide sequences design rules toward the ultimate goal of rational nanomaterials design.

Sequence-dependent structure/function elucidation of peptide-enabled nanoparticles using a combined experimental/computational approach<br />

249th National Meeting (2015)

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