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Identification and Development of Novel Wnt/β-Catenin Signalling Inhibitors

Identification and Development of Novel Wnt/β-Catenin Signalling Inhibitors
Identification and Development of Novel Wnt/β-Catenin Signalling Inhibitors
With an ever-aging population the risk of developing cancer is greater than ever. The WNT/β catenin signalling pathway has been highlighted as a key pathway in cancer development and furthermore, is an attractive therapeutic target. However, the number of drugs targeting β-catenin is limited due to various factors and claimed small molecule modulators often have inherent problems in specificity of mode of action or a lack of evidence, biophysical, KD, crystallography or otherwise. Therefore, there is dire need for therapeutic intervention of β-catenin. In this thesis, we review the literature of reported and putative β-catenin inhibitors and highlight the vast majority of them are flagged by computational filters such as PAINs and Brenk filters. Furthermore, we investigate these reported inhibitors by biophysical methods such as Differential Scanning Fluorimetry (DSF) and Isothermal Titration Calorimetry (ITC) and show that in our hands none of them engage with recombinant purified β-catenin. Herein we report the discovery of novel small fragments that are β-catenin stabilisers. These fragments have been validated by orthogonal biophysical techniques such as DSF and Saturation Transfer Difference Nuclear Magnetic Resonance (STD-NMR) and ITC. Furthermore, we report the synthesis of Carnosic acid derivatives as novel βcatenin destabilisers. Finally, we undertake in silico HTVS to identify top computational compounds to test against β-catenin in vitro.
University of Southampton
McCoy, Michael Arron
151681b5-f1e3-4ace-83ae-adc2755f9af9
McCoy, Michael Arron
151681b5-f1e3-4ace-83ae-adc2755f9af9
Baud, Matthias
8752d519-3d33-43b6-9a77-ab731d410c2e
Tavassoli, Ali
d561cf8f-2669-46b5-b6e1-2016c85d63b2

McCoy, Michael Arron (2023) Identification and Development of Novel Wnt/β-Catenin Signalling Inhibitors. University of Southampton, Doctoral Thesis, 200pp.

Record type: Thesis (Doctoral)

Abstract

With an ever-aging population the risk of developing cancer is greater than ever. The WNT/β catenin signalling pathway has been highlighted as a key pathway in cancer development and furthermore, is an attractive therapeutic target. However, the number of drugs targeting β-catenin is limited due to various factors and claimed small molecule modulators often have inherent problems in specificity of mode of action or a lack of evidence, biophysical, KD, crystallography or otherwise. Therefore, there is dire need for therapeutic intervention of β-catenin. In this thesis, we review the literature of reported and putative β-catenin inhibitors and highlight the vast majority of them are flagged by computational filters such as PAINs and Brenk filters. Furthermore, we investigate these reported inhibitors by biophysical methods such as Differential Scanning Fluorimetry (DSF) and Isothermal Titration Calorimetry (ITC) and show that in our hands none of them engage with recombinant purified β-catenin. Herein we report the discovery of novel small fragments that are β-catenin stabilisers. These fragments have been validated by orthogonal biophysical techniques such as DSF and Saturation Transfer Difference Nuclear Magnetic Resonance (STD-NMR) and ITC. Furthermore, we report the synthesis of Carnosic acid derivatives as novel βcatenin destabilisers. Finally, we undertake in silico HTVS to identify top computational compounds to test against β-catenin in vitro.

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More information

Submitted date: 17 May 2022
Published date: January 2023

Identifiers

Local EPrints ID: 473328
URI: http://eprints.soton.ac.uk/id/eprint/473328
PURE UUID: 43828882-1625-451f-ae15-065d8bf92044
ORCID for Matthias Baud: ORCID iD orcid.org/0000-0003-3714-4350
ORCID for Ali Tavassoli: ORCID iD orcid.org/0000-0002-7420-5063

Catalogue record

Date deposited: 16 Jan 2023 17:31
Last modified: 17 Mar 2024 03:41

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Contributors

Author: Michael Arron McCoy
Thesis advisor: Matthias Baud ORCID iD
Thesis advisor: Ali Tavassoli ORCID iD

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