Abstract The broad aim of this thesis is to structurally and functionally explore two α-conotoxins, from venomous sea snails, Vc1.1 and RgIA, in the hope of improving their journey to becoming analgesic therapeutics (introduction to conotoxins in Chapter 1). Vc1.1 is a two-disulfide peptide that is of interest as a potential therapeutic for the treatment of neuropathic pain. Despite investigations, limited structure-activity relationships have been conducted on this α-conotoxin. Consequently there is restricted insight into the interaction of this peptide with one of its analgesic targets, the α9α10 nicotinic acetylcholine receptor (nAChR). Late in this PhD project, the GABAB receptor was implicated as the possible target for conotoxins in neuropathic pain relief. However, there is still debate in the literature with regard to the true target of Vc1.1 and the α9α10 nAChR is still believed to be the target by some groups. This thesis predominantly focuses on the α9α10 nicotinic acetylcholine receptor. Chapter 4 of this thesis presents an extensive series of mutational studies in which all residues except the conserved cysteines were mutated separately to Ala, Asp or Lys (materials and methods described in Chapter 3) and examined using NMR spectroscopy (theory of NMR presented in Chapter 2), to determine the effects of the mutations on the structure of Vc1.1. The structural fold was found to be preserved in all peptides except where Pro was substituted. Chapter 5 explores the effect of these mutations on the blocking of acetylcholine (ACh)-evoked membrane currents at the α9α10 nAChR. Electrophysiological studies showed that the key residues for Vc1.1’s activity are Asp5-Arg7 and Asp11-Ile15, as changes at these positions resulted in the loss of activity at the α9α10 nAChR. Interestingly, the S4K and N9A analogs were more potent than Vc1.1 itself. Hence, Chapter 6 describes a second generation of mutants that was synthesized, namely N9G, N9I, N9L, S4R and S4K+N9A, all of which were more potent than Vc1.1 at both the rat α9α10 and the human α9/rat α10 hybrid receptor, providing a mechanistic insight into the key residues involved in eliciting the biological function of Vc1.1. The most potent analogs were also tested at the α3β2, α3β4 and α7 nAChR subtypes to determine their selectivity. All mutants tested were most selective for the α9α10 nAChR. These findings provide valuable insight into the interaction of Vc1.1 with the α9α10 nAChR subtype and will help in the further development of Vc1.1 or its analogs as drugs. However, despite peptides exhibiting high degrees of potency and selectivity, such as Vc1.1 and RgIA, they are potentially hindered in their development as drugs due to their stability and bioavailability limitations, leading to invasive delivery techniques. Chapter 7 presents a range of cyclic RgIA analogs, tested at their targets the α9α10 nAChR and the GABAB receptor, that retain their activity and increase their stability in human serum relative to non-cyclic RgIA. NMR spectroscopy was used to determine the structure of the non-cyclic peptide and the cyclic peptide to confirm similarities in the global fold of the peptide. Structural perturbations and reduced activities were observed for cyclic RgIA analogs cyclized via linkers composed of three and four residues. Analogs with five, six and seven residues showed no structural perturbations, but differences in their activities at the different receptors. Because cRgIA-6 showed high potency for the GABAB receptor and lower potency for the α9α10 nAChR, this study has identified a GABAB selective peptide. Additionally, because the cRgIA-7 showed high potency for the α9α10 nAChR and low potency for the GABAB receptor, a α9α10 nAChR selective analog has also been identified. With improvements in these peptides against enzymatic attack, they show great potential on their path to becoming orally available analgesics as they may be able to withstand enzymatic conditions in the stomach.
| Identifer | oai:union.ndltd.org:ADTP/280763 |
| Creators | Reena Halai |
| Source Sets | Australiasian Digital Theses Program |
| Detected Language | English |
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