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Synthesis of surface functionalized nanoparticles for biorecognition, and controlled interactions with proteins

Rui Hong, University of Massachusetts Amherst


Bionanotechnology provides an attractive and unique arena for chemists, biologists and physicists due to its interdisciplinary nature. This thesis work has focused on using synthetic chemical tools to functionalize nanoparticles for biological applications. To this end, a ligand system featuring poly(ethylene glycol) (PEG) segments and chain-end functionalities was developed. These ligands were utilized to functionalized nanoparticles with different cores, including metallic (Au), semiconductor (CdSe and CdSe/ZnS), and magnetic (FePt and iron oxide) materials. Using these surface tailored nanoparticle scaffolds, surface binding of nanoparticles with enzyme α-chymotrypsin (ChT) was systematically studied. The ChT-nanoparticle interaction was characterized as electrostatically driven and reversible. Importantly, control over ChT structure and function was demonstrated on three levels: no binding, binding and denaturation, and binding without denaturation, dictated by the nanoparticle surface monolayer composition. The monolayer of nanoparticles can be tailored to not only control protein (ChT)-nanoparticle interactions, but also impact enzyme-substrate interactions, which results in enhanced ChT chemoselectivity towards substrates with different charges. In addition, the PEGylated nanoparticles have been explored to stabilize enzyme to stresses found in real-world bio-catalysis. The combination of the unique attributes of the nanoparticle cores and the function of the monolayer periphery provides numerous opportunities in creation of multi-functional nano-materials that are useful in biological and material applications.

Subject Area

Organic chemistry

Recommended Citation

Hong, Rui, "Synthesis of surface functionalized nanoparticles for biorecognition, and controlled interactions with proteins" (2006). Doctoral Dissertations Available from Proquest. AAI3215893.