Structural Elucidation in Biomolecules by Nanometal Surface Energy Transfer Contact Points

Optical technology in biophysics has seen significant growth with development of high resolution techniques, like single-molecule FRET, to investigate biological structures under native conditions. Additionally, with the rise in gold nanoparticle use in drug delivery, bioassays, and intracellular tracking, Nanometal surface energy transfer (NSET) applications have also improved since its limited beginnings on 2nm gold nanoparticles. This dissertation aims to further exploit the surface plasmon – organic dye coupling properties by investigating a series of nucleic acid secondary structures with modified gold nanoparticles and fluorophores as structural contact points. Chapter 1 and Chapter 2 introduce the importance of tracking nucleic acid structures by describing their essential roles in biology as well as state-of-the-art techniques to monitor various conformers. In Chapter 3, gold nanoparticle-based aptamer sensors are investigated and manipulated to detect a multi-magnitude range of target concentrations. It is observed that the aptamer's degree of exposure to the target predictably decreases the limit of detection in optical aptasensors. In sequential Chapters 4-6, a variety of G-quadruplex structures are investigated for their structural characteristics as well as their more global, cooperative relationships. The gold nanoparticle acts as a distant-dependent quencher for these surface-appended, dynamic nucleic acid sequences, in which the intensity of a DNA-functionalized dye distinguishes the specific G- quadruplex structure. In Chapter 7, NSET is pushed to further limits, by adding a distant- dependent contact point to the gold nanoparticle surface in the form of a FRET pair, to build a theorem for an NSET-FRET hybrid system for optical triangulation. The observed quenching of the donor lifetime in the presence of additional decay pathways confirms the efficacy of the NSET-FRET hybrid system and lays the groundwork for a mathematically predictable distance dependence model.