Publication Date


Date of Final Oral Examination (Defense)


Type of Culminating Activity


Degree Title

Master of Science in Chemistry



Major Advisor

Owen McDougal, Ph.D.


Lisa Warner, Ph.D.


Matthew King, Ph.D.


The work presented in this thesis contributes to ongoing development of an efficient workflow for identification of lead compounds, based on the molecular scaffold of α-conotoxin MII, for drug therapies targeting nicotinic acetylcholine receptors. Nicotinic acetylcholine receptors (nAChRs) are pentameric, ligand-gated ion channels with distribution throughout the central nervous system and are implicated in a variety of neurological diseases including schizophrenia, nicotine addiction, Alzheimer’s disease, and Parkinson’s disease. However, ligand effect on nAChR function is not well understood. Consequently, drug therapies for neurological diseases either do not exist, or have short-lasting efficacy and/or severe side effects. Barriers to the comprehension of nAChR function, pharmacology, and detailed knowledge of their ligand binding domains are limited due to difficulties expressing functional receptors in heterologous systems, inability to crystallize their structures, and difficulty efficiently assessing predicted binding paradigms using current wet-lab experimental methods. To better understand the effect α-CTx binding to nAChRs has on cell signaling, we utilized a combination of computational tools to predict binding affinity and a PC12 cell-based assay the ability to qualitatively assess real-time bioactivity of predicted ligands. The computational tools permitted screening of α-CTx MII analogs for optimal characteristics for binding to the α3β2 nAChR isoform, producing the KTM peptide. The PC12 cell assay was developed to quickly and economically pre-screen ligands for nAChR bioactivity qualitatively prior to resource-intensive electrophysiology or animal studies, increasing efficiency of vii investigations into nAChR binding and function. The work in this thesis demonstrates the merit of computational prediction in nAChR ligand binding, provided an accessible qualitative bioassay to efficiently validate predicted ligand bioactivity on nAChRs, and presents a case study of the rationally designed KTM peptide including structure activity relationship results in cell-based assay and electrophysiology experiments. Future studies will involve using computational programs to identify pharmacophore features required as ligand binding determinants to discover small molecule scaffolds based on peptide model compounds, and characterizing these small molecules for desired activity in cell lines heterologously expressing disease-relevant nAChR subtypes.



Included in

Biochemistry Commons