Characterization of alcohol dehydrogenase YqhD, and exploration of the origins of fluorine nuclear magnetic resonance chemical shifts in proteins

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Authors
Ellis, Jonathan M.
Advisors
Mitchell-Koch, Katie R.
Bann, James G.
Issue Date
2018-07
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Thesis
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Abstract

Alcohol Dehydrogenase YqhD acts as a useful enzyme for the purpose of conversion of alcohols to aldehydes, and visa-versa. It acts on a wide range of substrates, and as such provides a potentially useful platform for production of a variety of compounds used in synthesis, biofuels, and more. To aid in future engineering efforts, biophysical characterization of YqhD was conducted, including exploration of the role of the metal center by Michaelis-Menten kinetics and FRET-based analysis of cofactor binding. To help validate previously conducted molecular dynamics simulations, 19F-NMR was employed to observe potential changes in protein structure and dynamics upon binding of zinc, cofactor, and substrate. However, this labeling technique suffers from so-called “The Assignment Problem” of NMR, which describes determining which resonance in a NMR spectrum corresponds to which residue in a labeled protein. In an effort to expand techniques available to those interested in 19F-NMR, a sitespecific labeling technique was further developed and shown to be usable for a single resonance assignment of the acquired YqhD spectra. One of the “holy grails” of computation chemistry in regards to NMR is to perform accurate assignments of NMR chemical shifts in macromolecular systems. To this end, a reasonably exhaustive set of QM calculation methods were tested to determine their accuracy in predicting the 19F-NMR spectra of small molecule sidechain analogues of commonly employed labeling amino acids. This information was then used to generate a large dataset describing the influence of dielectric and external electric fields on a 19F-NMR resonance. With this information, the PFNMR software package was developed in an effort to perform resonance assignments on the IFABP and PapD proteins in a fully computational fashion, with promising initial success.

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Thesis (M.S.)-- Wichita State University, College of Liberal Arts and Sciences, Dept. of Chemistry
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Wichita State University
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