Graduate College. iv ACKNOWLEDGEMENTS The work described in this thesis was made possible by the individuals who came before me, trained me, and worked alongside me. I would like to acknowledge Matthew Turner for his preliminary foundational work with PC12 cells at BSU, in developing a decontamination method for conotoxins, and his thorough literature reviews. Dr. Tim Andersen gave years of collaboration in the development of the DockoMatic software, and Dr. Thomas Long gave us his creativity

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... produce the GAMPMS application that led to the sequence for KTM. All of this led to the computational chemistry by Dr. Matthew King that the work in this thesis is based on. I would like to thank Paul Phillips for his foundational literature review, James Groome for providing his time and resources for electrophysiology work, Joe Dumais for his consultation with NMR, and Shin Pu for his consultation with MS-MS. I would also like to thank the members of my graduate committee, Drs. Owen McDougal, Lisa Warner, and Matthew King, for their guidance, input, correction, and insight. Dr. Owen McDougal was a valuable resource of thorough knowledge in the field of conotoxins and wisely guided my placement onto this project. Dr. Lisa Warner offered her NMR expertise including extensive troubleshooting with computer programs including CCPNMR, CYANA, and others. Dr. Matthew King provided proficiency and training in Dockomatic and other computational chemistry programs to help pave the way for the future of this work. access to graduate student stimulus funds that made this work possible. Lastly, I would like to describe my personal thanks for a few key individuals. Owen McDougal taught me to be confident in myself as a scientist. Thank you for being transparent, gently but realistically teaching me the intricacies of the system, and never standing to see me sad. You were exactly what I needed in this journey. Lisa Warner reminded me of the impact of being good-humored no matter how stressful things are. You gave me the peace of making everything relatable. When my surroundings were turbulent, you helped keep my eyes at an inspired perspective. Matt King was my quiet and steady support. You gave me precisely the tools I needed without distraction and deserve a gold medal in being there for us. James Groome has seen my best and worst times and was only ever compassionate and merciful. You showed me that it really is possible to overcome obstructions, no matter how big or numerous. Sometimes you just need someone to show you how it's done. Matthew Turner advocated for me at all stages. I only hope someday I will have the scientific wit and critical thinking that you do. vi ABSTRACT 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.