Theses - Chemistry
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Item Open Access Advancing Fluorescence Microscopy Techniques for Volumetric Whole-cell ImagingZhang, ZiweiOne revolution in the last decade has been the application of new imaging methods to modern biology, revealing new insights into cellular structure and dynamics. However, imaging methods capable of three-dimensional (3D) imaging at high spatial and temporal resolution are still lacking. This thesis describes two projects aimed at advancing volumetric whole-cell imaging based on fluorescence microscopy. The first project establishes a robust single-molecule localisation microscopy (SMLM) pipeline for volumetric imaging in the whole cell using the double-helix point spread function (DH-PSF) approach. The practical challenges associated with this method, such as aberration- and drift-induced inaccuracies, were comprehensively evaluated, and methods were developed to address all these problems. With a novel spontaneous blinking PAINT (Point Accumulation for Imaging in Nanoscale Topography) dye, HMSiR-Hoechst, super resolved SMLM images of DNA throughout the entire mammalian cell nucleus were obtained. The second project involved the design and construction of an epi-illumination selective plane illumination microscopy (eSPIM) system capable of rapid volumetric multi colour live fluorescence imaging of cellular samples. This system was one of the first of its kind in Europe, demonstrating excellent performance by yielding high resolution in line with established standards. A comprehensive comparison of eSPIM with three alternative volumetric imaging modalities was conducted, focusing on the dynamics of DNA and Heterochromatin Protein 1 beta (HP1β) within live mouse embryonic stem cells (mESCs), demonstrating the superior performance of the eSPIM. Collectively, this work makes a significant contribution to volumetric fluorescence microscopy, extending our capability to dissect and visualise cellular structure and interaction in whole-cell in 3D.Item Open Access Improving de novo molecule generation for structure-based drug designThomas, Morgan; Thomas, Morgan [0000-0002-1610-3499]*De novo* molecule generation for drug design has seen a resurgence in recent years, mostly due to the rapid advances in machine learning (ML) algorithms that utilise deep neural networks, resulting in a plethora of ML-based generative models. However, there is often a large disparity in published evaluations and applications of such approaches compared to the practical needs of real drug design projects (for example, optimizing QED *versus* optimizing binding affinity commonly approximated by structure-based approaches). Moreover, the density of approaches and often lack of relevant, standardized objectives makes it difficult to truly discern “state-of-the-art”. The work in this thesis aims to address some of these issues and improve the applicability and evaluation of *de novo* molecule generation for practical drug design. The first research chapter will outline the design and use of an open-source python-based software named MolScore. This configurable suite of scoring functions (including an interface to 5 docking algorithms and ~2,300 trained bioactivity models) can be used to design difficult yet relevant drug design objectives for standardized comparison, or practical usage with generative models. In addition, MolScore includes a graphical user interface to improve usability and a suite of common evaluation metrics to evaluate *de novo* generated molecules. Next, MolScore was implemented to compare the use of docking as a more difficult objective function for REINVENT (a generative model for goal-directed *de novo* molecule generation), as opposed to more commonly used predictive models of molecule bioactivity. This resulted in increased diversity of *de novo* molecules and improved coverage of known bioactive chemical space. However, the added computational expense required for generative model optimization is a practical disadvantage of docking as a scoring function. To address the computational expense of optimizing docking scores, a hybrid reinforcement learning algorithm (Augmented Hill-Climb) is proposed to improve the learning efficiency of language-based generative models. This significantly reduced the computational runtime while maintaining the chemical desirability of *de novo* molecules. Augmented Hill-Climb displayed superior efficiency against four other commonly used reinforcement learning algorithms, also displayed in an alternative model architecture. It was then benchmarked against 22 various generative models showing the best sample efficiency when additionally constraining for chemical desirability. Overall, the work outlined in this thesis contributes to the field of computational drug design by providing software, algorithmic developments, and benchmark results for different *de novo* molecule generation approaches.Item Embargo Generating artificial metalloenzymes containing new-to-nature organometallic cofactors via controlled ligand exchange and microfluidic screening technologiesKlein, Oskar James; Klein, Oskar James [0000-0003-2213-8003]Artificial Metalloenzymes (ArMs) containing non-natural organometallic cofactors have commanded increasing attention for their ability to catalyse transition-metal dependent transformations with the selectivity and mild conditions associated with enzymes. This work investigates novel ArMs where an organometallic cofactor has been introduced *via* ligand exchange reactions, thus ensuring an intimate link between the first and second coordination-sphere, with the latter being dictated by the protein fold. Further, the development of a high-throughput microfluidic screening platform is presented, with the aim to facilitate efficient directed evolution. The first chapter gives a theoretical description of the matter covered by this thesis and reviews the relevant fields, including considerations for the formation of ArMs, *in vitro* directed evolution and a brief discussion of transition metal catalysis, focusing on ruthenium. The second chapter covers the practical aspects of the work conducted, including detailed descriptions of synthetic processes as well as biochemical and microfluidic techniques. The third chapter details the design, synthetic challenges and characterisation of a range of substrate molecules used for the establishment of fluorescence assays for different ArM activities. Particular focus is placed on the synthesis and use of charged substrates that do not leak from the aqueous phase when used in water-in-oil droplet microfluidics. The fourth chapter focuses on the formation of ArMs from organometallic complexes. A systematic study is presented, describing how the steric and electronic properties of a ruthenium piano-stool complex, carrying a key bipyridine ligand, led to various speciation of cytochrome *b*562. Applying findings from this study, the scope of organometallic fragments that could be introduced was further expanded to include new metal centres and ligands. The resulting conjugates were characterised and investigated for catalytic activity. Finally, a method for evolving cofactor recognition using pre-fluorescent complexes is presented. The fifth chapter details the development of a microfluidic workflow compatible with the ArMs used in this thesis, aiming to rapidly encapsulate, express and sort large genetic libraries of ArMs and thus enable directed evolution. Coupling of the genotype and phenotype is achieved by covalent attachment to hydrogel beads, mitigating the possibility of catalytic poisoning when using an *in vivo* approach. The concluding chapter summarises the key results of this work and gives perspective on potential future developments.Item Restricted Genetic engineering of structural colour in the model organism, Flavobacterium IR1Caton Alcubierre, Laura; Caton Alcubierre, Laura [0000-0003-2905-3045][Restricted]Item Open Access The Design, Synthesis and in vitro Evaluation of Proteolysis Targeting Chimeras (PROTACs) for the Degradation of Protein Arginine Methyltransferase 1Martin, PoppyProtein arginine methyltransferase 1 (PRMT1) is a protein responsible for the asymmetric dimethylation of arginine. PRMT1 is upregulated in a wide range of cancers and the reduction of PRMT1 activity reduces cell proliferation and tumour growth in cell and animal models of cancer. A reduction in PRMT1 can also sensitise cancer cells to other treatments. Therefore, targeting PRMT1 is a promising therapeutic strategy in cancer treatment. Published inhibitors for PRMT1 show poor selectivity and dose-limiting toxicities that have precluded their translation to the clinic. The degradation of PRMT1 using a PROTAC may be superior to inhibition as PROTACs can act catalytically at a low dose. PROTACs can also exhibit high selectivity and cause a more pronounced functional outcome compared to inhibition. In this thesis, PRMT1 is explored as a target protein for PROTAC-induced degradation. The endogenous properties of PRMT1 were evaluated and PRMT1 was determined to be amenable to degradation by a PROTAC. PROTACs were designed that comprised a PRMT1 ligand, a linker and an E3-ligase ligand. Ten PROTACs that recruit the VHL E3-ligase and six PROTACs that recruit the CRBN E3-ligase were synthesised. The degradation of PRMT1 was assessed by Western blot and degradation was not observed for the PROTACs synthesised. Suitable pharmacokinetic properties and target engagement have been shown for selected candidates by the detection of the downstream effects of PRMT1 inhibition and by a NanoBRET assay for E3-ligase binding. Regioselectivity challenges in the synthesis of the CRBN-recruiting PROTACs led to the isolation of a heterobifunctional molecule with the linker attached to the binding pharmacophore of the CRBN ligand. This molecule was found to degrade PRMT1 and is proposed to be a monomeric degrader that destabilises the structure of PRMT1 upon binding. This thesis details a novel approach to degrade PRMT1 using a PROTAC and provides insights that may assist the rational design of PROTACs that target PRMT1 in the future.Item Embargo Design and Frabication of Optical Li+ Sensors for Application in Li-ion BatteriesFrancis, HaydnLi-ion batteries have redefined expectations for consumer electronics and are the key technology in enabling the electrification of road transport. Their contribution to decarbonisation only stands to increase in the coming decades as demand for Li-ion batteries continues to soar. However, as production continues to accelerate, maximising device-level level sustainability over the lifetime of cells, modules, and battery packs is of increasing importance. Currently, there is a broad suite of techniques available in laboratory settings for the analysis of Li-ion battery performance and degradation during operation. Studying batteries using these techniques has led to the design of safer, longer-lasting batteries over the past few decades. However, most of these techniques use large and/or expensive instrumentation or require the design of bespoke cells and are therefore not applicable as methods for monitoring commercial battery systems in the field. Currently, only a small collection of non-disruptive diagnostic techniques are available for these applications. In addition, these techniques generally measure broad metrics, which are extrapolated using statistical methods to estimate and predict cell performance, often resulting in systematic underutilisation of battery systems. Optical techniques offer a potential solution to this problem owing to their low-cost, facile integration as part of commercial battery systems and their potential to monitor a range of mechanical, thermal, and chemical parameters through the application of optical fibres. By providing specific and detailed data in real-time, optical techniques coupled with a smart battery management system have the potential to improve battery lifetimes, reduced safety risks, and facilitate more advanced characterisation ahead of end-of-life protocols (e.g., re-use, recycling, etc). In this thesis, we discuss the development of a novel optical sensing platform for monitoring [Li+] in battery electrolytes. The first chapter introduces key concepts around the basic operation of Li-ion batteries and the degradation processes that lead to loss of performance during their operation. Following this, the range of *in situ* and *in operando* techniques that have facilitated our current understanding of processes occurring inside Li-ion batteries are discussed as well as the state-of-the-art in the application of optical techniques. This chapter ends with a summary of the thesis and its objectives and serves as an introduction to the context in which this work was originally formulated. The second chapter begins with an introduction to the field of optically active organic molecules, ionophores, and their convergence to form highly selective and sensitive optical chemosensors. Subsequently, the design, synthesis, and characterisation of two novel Li+-selective fluorescent chemosensors based on a naphthalene diimide core are described. Although both displayed poor solubility in salt-solvent systems reflective of the conditions in a Li-ion battery electrolyte, they were deemed to be a promising starting point for the development of a solid-supported chemosensor-based optical sensing platform for our applications. Chapter III starts with a summary of the fabrication and operation principles of planar and nanoparticle optodes as well as their application as part of optical fibre sensors. Following this is a discussion of potential strategies for the immobilisation of a chemosensor onto a solid support for applications as an optode sensor. Subsequently, the chapter describes the optimisation of experimental parameters towards the development of a fabrication procedure for planar optodes functionalised with one of the novel chemosensors synthesised in Chapter II. The final planar optodes used a silica-based substrate loaded with a mesoporous surface film, which is functionalised with a modified derivative of the chemosensor. Characterisation of the planar optodes demonstrated their promising properties for monitoring [Li+] selectively in concentration ranges and solution conditions relevant to Li-ion battery electrolytes. This chapter also summarises attempts to apply the same fabrication procedure for the functionalisation of optical fibres to form ‘dip probes.’ However, these were largely unsuccessful. To further characterise the properties of the optode sensor in emission mode, the planar optodes were integrated as part of microfluidic devices. This provided precise control over liquid samples on the optode surface and enabled full characterisation of their Li+-sensing capabilities in emission mode. Chapter IV provides a summary of this data, which showed the planar optodes to possess the necessary sensitivity and selectivity for application as an emission mode concentration sensor in battery electrolytes. In addition, the platform was shown to demonstrate strong cyclability, a rapid time response, and a level of spatial resolution that suggested the optodes could be applied for dynamic chemical imaging using fluorescence microscopy. Chapter V is the final chapter and describes the application of the optode-based microfluidic devices for two proof-of-concept experiments. Firstly, ex-situ [Li+] measurements were taken using the devices on a pristine electrolyte and electrolyte extracted from a Li-ion pouch cell after cycling. These results provided a quantitative indication of bulk Li+ depletion in the electrolyte during cycling with a comparable level of accuracy to ICP-OES measurements run in parallel. Secondly, simple experimental conditions were designed to establish the ability of the optodes to track the evolution of Li+ concentration gradients in solution with time. These experiments yielded the first recorded example of spatial Li+ tracking using a solid-supported optical sensor to our knowledge. Modelling of the diffusion data showed that the experimental results could provide a comparative estimation of the Li+ self-diffusion coefficients for different solvent systems.Item Embargo Molecular Encapsulation of Conjugated Polymers for Organic ElectronicsMoiseanu, Teodora; Moiseanu, Teodora [0000-0003-2400-1772]Conjugated polymers have been the subject of extensive research, particularly for their application in the field of organic electronics. Attributes such as their semiconducting nature, solution processability, degree of flexibility, and infinite tunability have led to their successful implementation as light-harvesting or light-emitting materials. In the first chapter, we introduce and describe several key concepts within the area of organic electronics. These concepts include the understanding of how conjugated polymers function and their relevance within the field. We explore the various applications with detailed device characteristics. Additionally, we examine various strategies for modifying monomers to adapt and control the molecular bandgap of the polymers to suit specific applications. Furthermore, we consider the influence of conjugation length and aggregation on the electronic properties and device performance. Lastly, we discuss different synthetic procedures employed to achieve high molecular weight conjugated polymers. The second chapter begins with the introduction of different techniques to lower the formation of aggregates in conjugated polymers. It describes both non-covalent and covalent encapsulations that have been previously employed, offering examples of their efficacy in reducing nonradiative decay processes. Past research on molecularly encapsulated conjugated polymers has extensively focused on molecular backbones such as diketopyrrolopyrrole (DPP), naphthalene diimide (NDI) and perylene diimide (PDI). In the context of this work, the research is centered around narrow bandgap encapsulated conjugated polymers based on benzodithiophene (BDT). Consequently, this chapter delves into BDT-based conjugated copolymers and their naked (unencapsulated) counterparts. This study highlights that molecular encapsulation serves to suppress intermolecular interactions, resulting in polymers exhibiting a lower degree of energetic disorder and increased spacing between polymer chains. However, it is noteworthy that the photoluminescence quantum yield (PLQY) in the solid state is unexpectedly lower (1%) compared to previous studies. Nevertheless, when assessing the performance of devices in comparison to the record breaker PM6:Y6 system, our materials demonstrate remarkably high efficiencies. These outcomes prompt a deeper investigation into the reasons underlying the reduced emissivity with encapsulation, and whether this phenomenon is linked to the BDT core or the acceptor comonomer component. The third chapter focuses on increasing the order within the polymer backbone by having a higher density of encapsulation throughout the entire polymer chain. To achieve this objective, this chapter explores the synthesis of BDT-based encapsulated conjugated homopolymers, and their reference counterparts. The control of interpolymer distance is achieved through various ways including: the nature of the solubilising chain, the nature of the encapsulating chain, and the length of the encapsulated chain. Through ultraviolet-visible (UV-Vis) and photoluminescence (PL) measurements, our studies reveal that encapsulation mitigates aggregation to a certain extent. Nevertheless, even with increasing the distance between polymer chains, the emission remains suppressed. Notably, as excimer formation can be discarded due to the reduced cross-communication, our findings point towards nonradiative loss being attributed to an intramolecular process. Through thorough transient absorption (TA) measurements, we identify this loss as being linked to polaron pair formation. Collectively, these results lead us to the conclusion that BDT-based polymers might not be as suitable for solar cell applications as was previously believed, with the root cause lying in intricate intramolecular processes that prove challenging to control effectively. The final chapter (chapter IV) explores a distinct property offered by molecular encapsulation. It firstly describes chirality within conjugated polymers, providing examples of materials holding higher dissymmetry factors of absorption and emission, albeit at the cost of the conjugation length of these polymers. Therefore, the research focus was shifted towards the synthesis of main-chain planar chiral conjugated polymers, aiming to achieve a high degree of chiroptical properties. Specifically, the study centeres on [n]paracyclophane-based ([n]PC) conjugated polymers, designed to investigate various effects. These include altering the cyclophane chiral centre by changing the ansa unit, modifying the polymer morphology by changing the side chains, and varying the choice of comonomers used for polymerisation to encompass a broader spectal range. It was demonstrated that the chiral response can be predominantly influenced either by the size of the encapsulating chain, resulting in more twisted conjugated polymers, or by the morphology of the sample, with higher responses observed for less crystalline materials. Furthermore, the synthesis of the paracyclophane comonomers is enantioselective, rendering it more suitable for industrial applications and thus next-generation circularly polarised organic light-emitting diodes (CP-OLEDs) materials.Item Embargo Characterisation and Detection of P53 AggregatesWu, YunzhaoP53 is a tumour-suppressing protein whose primary function is to protect the integrity of the genome, specifically by regulating DNA repair, cell cycle arrest, cell proliferation, and apoptosis. Wild-type (WT) p53 has multiple aggregation-prone regions and can form amyloid aggregates. Some mutants of the p53 protein, such as the R248Q mutant, exhibit higher aggregation propensity than the WT. P53 aggregation is associated with loss-of-function, gain-of-function, and dominant-negative effects of the protein and thus plays a crucial role in cancer. Understanding the properties of p53 aggregates and their pathological implications provides new insights into cancer biology and may lead to novel diagnostic and therapeutic strategies. Previous studies on p53 aggregates mainly focused on the properties of bacteria-derived p53 core-domain fragments, which have different post-translational modifications from human p53 and may behave distinctly from full-length p53 proteins. The p53 concentrations used in these studies were also higher than the physiological concentrations. Meanwhile, most kinetic studies on p53 aggregation employed microplate reader-based assays, which are limited in sensitivity and cannot provide morphological information about the aggregates. Hence, the biophysical properties of full-length p53 aggregates at physiological concentrations are not well characterised. Also, the detection of p53 aggregates in biopsies has not been demonstrated. In this thesis, a series of advances in single-molecule assays are presented to characterise full-length p53 aggregates and detect p53 aggregates in human plasma. Firstly, a single-molecule fluorescence microscope with flat-field illumination was constructed and characterised. Secondly, a Python-based computational suite for automated fluorescence image analysis was implemented. Based on these two techniques, the aggregation kinetics, membrane disruptive ability, and morphological features of insect cell-derived full-length WT and R248Q p53 aggregates were characterised. Specifically, p53 aggregation at physiologically relevant concentrations was found to be dominated by a nucleation-elongation process. Meanwhile, both WT and R248Q p53 aggregates exhibit membrane-disruptive abilities. Furthermore, a single-molecule array assay was developed to detect p53 aggregates in plasma samples, demonstrating p53 aggregates as a promising diagnostic biomarker for glioblastoma. The presence of p53 aggregates in the plasma samples of glioblastoma patients was validated using the single-molecule pull-down assay. The work presented in this thesis extends the understanding of full-length p53 aggregates and highlights the implications of p53 aggregates in cancer diagnosis.Item Open Access Chemical Softness as a Predictor for Reactivity at Metal SurfacesGunton, AmyHeterogeneous catalysis is an important global industry, but there are many gaps in our understanding of catalytic selectivity. Reactivity indices are helpful for predicting selectivity, and it would be useful to have a reactivity index which can be applied to metal surfaces and adsorbates. The local softness is a reactivity index based on Pearson’s theory of hard and soft acids and bases. It is the derivative of the local electron density with respect to the chemical potential, at constant external electric potential. It can be calculated simply for molecules or nanoparticles which have a band gap. However, the calculation for conductors is less straightforward. In this work, a method was developed to calculate the local softness of metal surfaces using density functional theory. This required a solution to the problem of increasing the chemical potential while keeping the external electric potential constant, which is difficult to do in charged cells with periodic boundary conditions. This problem was solved by correcting for a shift in energy reference with charge and by extrapolating to an infinitely sized unit cell. The local softness was visualised using isosurfaces and colourplots and was used to compare predicted reactivity between different sites on various metal surfaces. In order to get a measure of the softness of individual atoms on a surface, Bader’s theory of atoms in molecules was used to integrate the local softness over the regions of atomic volume. The resulting reactivity index, the atomic softness, was used to predict the adsorption energy of carbon monoxide on eighteen different metal surfaces. The local and atomic reactivity indices were also used to study directing effects for aromatic adsorbates on the Pt\{111\} surface. The local and atomic softness were found to be useful for predicting reactivity trends between different sites on metal surfaces and for adsorbates.Item Embargo Supramolecular Functional Materials Based on Cucurbit[8]uril-Enhanced π–π InteractionsChen, XiaoyiOn account of the dynamic and controllable nature, host-guest chemistry has been applied in research areas including drug delivery, sensing, catalysis, and nanotechnology. In particular, the cucurbit[n]uril (CB[n]) family of macrocyclic hosts has attracted considerable attention over the last decade. Advantages of CB[n]-based systems include compatibility with a wide guest scope of molecules, a high binding affinity that spans a wide range (10³ – 10¹⁵ M⁻¹), proven biocompatibility and stability in physiological conditions. In this thesis, for the first time, a new CB[8] binding mode is introduced as “CB-enhanced π–π interactions” in Chapter 2. Later, in Chapter 3, these interactions are further explored in the context of oligopeptide assemblies to form controlled heteropeptide dimers which are applied towards on-resin recognition of peptides and proteins with excellent recyclability and selectivity. The uptake and stabilisation of insulin prove a new route to room-temperature storage and utilisation of insulin. Then, in Chapter 4, cyclic peptide structures designed to form tight assemblies are investigated. Using CB[8]-enhanced π–π interactions, the assembly behaviours of CB-cyclic peptide complexes are studied within a constrained environment. The new host-enhanced π–π interactions are further exploited in the fabrication of supramolecular polymer networks in Chapter 5. Through careful selection of the second π-rich guest, the association and dissociation of the network are controlled to realise slow dissociation dynamics which result in glass-like properties being accessed for the first time in supramolecular polymeric materials. Last but not least, Chapter 6, a perspective of this thesis, demonstrates the development and utility of CB-enhanced π–π interactions within supramolecular and biological systems.Item Open Access A methodological framework to assess multi-pollutant personal air quality exposure for improved health associationsMartin, Elizabeth; Martin, Elizabeth [0000-0002-4743-2842]Current assessments link poor air quality to around seven million premature deaths worldwide annually. However, exposure studies, often utilising measurements from stationary outdoor instruments from sparse monitoring networks, cannot capture spatial heterogeneity or the fact that people spend significant fractions of their time indoors. This failure to assess the actual pollution exposure individuals receive leads to inaccuracies in pollution-health associations, potentially masking the factors that drive the observed health responses, resulting in misinformed policies. To address these limitations, a portable personal air quality monitor (PAM) was developed, allowing for the assessment of actual personal exposure to key pollutants: CO, NO, NO2, O3, and PM2.5, as well as providing location (GPS) and other parameters for time-activity assessment. The work in this thesis develops a framework, which, when applied to large scale fieldwork studies, is capable of disaggregating personal exposure by source and linking it to health parameters for hundreds of participants. At the core of the framework is a methodology for apportioning personal exposure into pollution generated by indoor sources and pollution generated by outdoor sources. This apportionment is achieved by employing a mass-balance model and estimating values of ventilation rates, indoor loss rates and indoor source characteristics, collectively referred to as “exposure determinants”. The framework was applied to data from the AIRLESS project, which involved the deployment of PAMs to 250 residents of Beijing and the surrounding area. Personal exposure to NO2, O3 and PM2.5 was found to be lower than that inferred from measurements from stationary outdoor reference instruments, suggestive of indoor losses for these pollutants. The results show differences between indoor-generated and outdoor-generated exposures, for example, 55% of participants’ exposure to CO was from indoor sources, compared with 30% of PM2.5. Apportioned exposure metrics, for example indoor- and outdoor- generated CO, while the same molecule, may be proxies for different mixtures of pollutants, which may have different health impacts. As expected, home ventilation rates were higher in the summer than in the winter, and the overall mean ventilation rate was estimated to be 3.12 hr-1, which is comparable to values found in the literature. Knowledge of the seasonal and demographic variability of exposure determinants will be crucial in the future modelling of total personal exposure at the population scale. This thesis concludes with the construction of a Linear Mixed Effects Model (LMEM), linking the novel exposure metrics and estimated exposure determinants to a health marker, in this case Peak Expiratory Flow (PEF). While the associations with personal exposure and PEF appear minimal in this study (concerns about the accuracy of self-reported PEF as an indicator are raised), it is expected that this framework will be of significant value when extended to directly examine the effects of the novel exposure metrics and estimated exposure determinants on other health parameters. This will provide insights into the source-related health effects of air pollution to drive more effective environmental policy.Item Open Access Drug discovery for misfolding diseases using structure-based iterative learningHorne, Robert; Horne, Robert [0000-0003-1534-2639]Computational methods such as machine learning hold the promise to reduce the costs and the failure rates of conventional drug discovery pipelines. This issue is pressing for neurodegenerative diseases, where the development of disease-modifying drugs has been particularly challenging. The high attrition rate of neurodegenerative drug discovery is especially acute for Parkinson’s disease, where no disease-modifying drugs have yet been approved. Numerous clinical trials targeting α-synuclein aggregation, a process implicated in Parkinson’s disease and other synucleinopathies, have failed, at least in part due to the challenges in identifying potent compounds in preclinical investigations. In Chapter 2, I describe machine learning approaches to identify small molecule inhibitors of α-synuclein aggregation to address this problem. Because the proliferation of α-synuclein aggregates takes place through autocatalytic secondary nucleation from fibril surfaces, we aim to identify compounds that bind the catalytic sites on the surface of the mature fibrillar aggregates (the end point polymers of the aggregation process). This prevents the formation of the toxic intermediate aggregate species, termed misfolded oligomers. Fibrils assume different structural polymorphs depending on the synucleinopathy, likely due to the different locations of the nervous system that these diseases occur within. Each tissue has an associated set of specific conditions which likely shape the final structure of the aggregates. Targeting these pathogenic polymorphs may help ameliorate disease progression more effectively than prior efforts. To achieve this goal, I use structure-based machine learning in an iterative manner to first identify and then progressively optimise secondary nucleation inhibitors. Training data for aggregation inhibition were obtained by an assay specifically isolating secondary nucleation, the major mechanism of toxic oligomer production. My results demonstrate that this approach leads to the facile identification of compounds which are two orders of magnitude more potent than previously reported ones. This initial work formed the basis of subsequent efforts to both expand the chemical space explored, and explore it more effectively, through application of generative modelling linked with reinforcement learning. I also increased the molecular parameters considered during the process of inhibitor optimisation in Chapter 3, accounting for aspects of pharmacokinetics as well as potency. This work addressed a number of shortcomings in the initial approach including restricted chemical space and a focus on potency alone. The initial method was reminiscent of the early stages of drug development, where large compound libraries are typically screened to identify compounds of promising potency against the chosen targets. Often, however, these compounds have a poor drug metabolism and pharmacokinetics (DMPK) profile, which are negative features that may be difficult to eliminate. To address this, the updated machine learning approach combines generative modelling and reinforcement learning to identify small molecules that perturb the kinetics of aggregation, thus reducing the production of oligomeric species, while also having high predicted blood brain barrier penetrance. This approach resulted in the identification of small molecules with good pharmacokinetic properties and potency against secondary nucleation. Misfolded protein oligomers generated via secondary nucleation are clearly of central importance in both the diagnosis and treatment of Alzheimer’s and Parkinson’s diseases. All the methods described here are designed to counter their formation, yet accurate high-throughput methods to detect and quantify oligomer populations are still needed. Invariably bulk aggregation is the metric that is tracked, and the oligomer population is then inferred. In Chapter 4 I present a novel single-molecule approach to detection and quantification of oligomeric species. The approach is based on the use of solid state nanopores and multiplexed DNA barcoding to identify and characterise oligomers from multiple samples. I study α-synuclein oligomers in the presence of several small molecule inhibitors of α-synuclein aggregation, as an illustration of the potential applicability of this method to assist the development of diagnostic and therapeutic methods for Parkinson’s disease. Finally, having created these pipelines for the development of α-synuclein aggregation inhibitors, I then sought to expand into other protein misfolding areas to demonstrate their generalisability as described in Chapter 5. The aggregation of tau into amyloid fibrils is associated with Alzheimer’s disease and related tauopathies. Similarly to synucleinopathies, different tauopathies are characterised by the formation of distinct tau fibril polymorphs. Brain homogenates were used to seed the generation of tau fibrils. The aim here was to create fibrils that replicate the polymorph formed in Alzheimer’s disease, thus mirroring the pathological aggregation mechanisms as closely as possible. Fibrils recovered from these efforts were capable of converting recombinant 0N3R tau into an Alzheimer’s fibril polymorph in a kinetic assay, as verified through cryo-EM structural analysis. Using this kinetic assay, I illustrate the iterative machine learning drug discovery method for tau aggregation in Alzheimer’s disease.Item Open Access Development of novel imaging technology to study cell signallingLi, BingCurrently it is difficult to study signalling on living cells at the single molecule level. One problem is that it is not possible to trigger signalling in a controlled manner and there is no effective method that can both introduce a precise amount of molecules onto or into a single cell at a specific position and then simultaneously image the cellular response using single molecule fluorescence. Here, we have developed local-delivery selective-plane illumination microscopy (ldSPIM) to address this issue. ldSPIM uses a nanopipette to accurately deliver individual proteins to a defined position. For single-molecule fluorescence detection, we implemented single-objective SPIM using a reflective atomic force microscope cantilever to create a 2 μm thick light sheet. Using this setup, we demonstrated that ldSPIM can deliver single fluorophore labelled proteins onto the plasma membrane of HEK293 cells or into the cytoplasm and characterise the interaction between cells and the delivered molecules in 3D at the same time. Then, we applied ldSPIM to characterize TLR4 activation and Myddosome signalling. The TLR4 agonist lipopolysaccharides (LPS) and aggregates of amyloid-β, which are supposed to be one of the key toxic species in Alzheimer’s disease, were delivered onto single macrophage stably expressing a MyD88-eGFP fusion construct. Whole-cell 3D light sheet imaging enabled the live detection of MyD88 accumulation and the formation of the Myddosome signalling complexes. Kinetics analysis of the trajectory of the assembly of individual Myddosomes suggested that amyloid-β triggered a significantly different Myddosome response compared with canonical LPS-triggered signalling. The nanopipette was also used to locally deliver interferon β onto mouse embryonic fibroblasts, to trigger the interaction between the interferon alpha and the beta receptor subunit 1 and the interferon alpha and beta receptor subunit 2. Lastly, in order to improve the light sheet imaging capability, we designed and assembled an epi-illumination SPIM (eSPIM), which is a next generation single-objective light sheet microscope with much faster scanning and is compatible with all kinds of sample dishes including multi-well plates. Overall, this thesis describes the building of new instrumentation to study cell signalling at the single molecule level, combining controlled delivery, via a nanopipette, and light sheet imaging, and the application of this instrumentation to study TLR4 signalling and the kinetics of Myddosome formation.Item Embargo Towards a Fundamental Understanding of Aqueous Organic Redox Flow Batteries – A Study of Degradation, Aggregation, and ReactivityHey, DominicRenewable energy sources such as wind, solar, and hydropower are becoming more prominent in the global energy mix. To address intermittency and ensure a reliable energy supply, grid-scale energy storage systems are crucial. Redox flow batteries (RFBs) are a useful tool for grid-scale energy storage and are able to address the intermittent nature of renewable energy sources. RFBs are well-suited for grid-scale applications due to their scalability, long cycle life, flexibility, separation of power and energy, rapid response, and, most importantly, safety. The most widely used RFB is the all-vanadium system, which contains toxic and expensive metal ions. Thus, organic RFBs are a promising alternative to replace the all-vanadium system. To date, many different organic molecules, including quinones, viologens, phenazines, and alloxazines, have been investigated as potentially cheaper RFB active molecules. While a few molecules have shown good performance, most organic molecules considered for RFBs have lower energy density and generally experience degradation, reducing cell lifetime. Thus, fundamental insight at the molecular level is required to improve their performance. In this work, different analysis methods were employed to understand the inter- and intramolecular interactions of the organic molecules in the negative electrolyte. *In-situ* methods based on various spectroscopic techniques were utilised: nuclear magnetic resonance (NMR), electron paramagnetic resonance (EPR); ultraviolet-visible (UV-Vis); and infrared (IR) spectroscopy. In the first results chapter, a detailed understanding of degradation processes is developed for the negative electrolyte flavin mononucleotide (FMN), a redox-active biomolecule which is readily derived from vitamin B2. These findings were then used to improve performance dramatically. FMN hydrolysis products were identified via *in-situ* NMR and EPR, and it was shown that these products give rise to the additional plateau seen during charging of a FMN-cyanoferrate battery. The redox reactions of the hydrolysis product are not reversible. However, capacity retention was observed even after substantial hydrolysis, albeit with reduced Voltaic efficiency, with FMN acting as a redox mediator. Critically, degradation was mitigated, and battery efficiency was substantially improved by lowering the pH from 14 to 11. *Ex-* and *in-situ* NMR analyses were then used to study 2,6-dihydroxyanthraquinone (DHAQ), a well-studied organic molecule in RFBs, and discussed in the second research chapter. The electrochemical degradation processes during cycling to high voltages and the electrochemical recomposition of decomposed DHAQ at low voltages are discussed. NMR was used to understand the previously unassigned electrochemical mechanisms, as well as the nature of the decomposition products. At high voltages, DHAQ decomposes to 2,6 dihydroxyanthrone (DHA) and its tautomer, 2,6-dihydroxyanthranol (DHAL). Suppression of the water solvent signal enabled the complete assignment of the obtained NMR spectra. Comparisons between deuterated water (D2O) and deionised water (H2O) were made as more NMR signals can be observed when H2O is used to avoid proton-deuterium exchange. DHAQ can then be electrochemically regenerated from the decomposition products through an oxidation to the dimer (DHA)24− followed by another low voltage oxidation. This electrochemical regeneration is a novel process that could only be identified by using the combination of *ex-* and *in-situ* NMR methods. In the third chapter, intermolecular processes, such as aggregation, were studied via *in-situ* UV-Vis and related to the electrochemistry of DHAQ. The intermolecular interactions become stronger with higher concentration, and due to the drive towards using highly concentrated electrolytes in practical RFBs, an understanding of these interactions is crucial. The combination of non-negative matrix factorisation (NMF), a principal component analysis, and UV-spectroscopy enabled detailed characterisation of the inter- and intramolecular processes. A tendency for DHAQ to aggregate was identified via an *ex-* and *in-situ* UV-Vis concentration study coupled with *ex-situ* NMR experiments. This aggregate appears to directly influence the radical concentration during cycling and increases the reduction potential. In the fourth research chapter, a novel *operando* IR cell was designed. With the cell, an analysis of the reaction kinetics and diffusion on the example system DHAQ is possible. The combination of microscopy and IR spectroscopy allowed for the direct targeting of carbon electrode fibres. Thus, the interfacial reactions of DHAQ on the carbon electrodes were better understood. Additionally, in combination with the line scan and mapping tools of the set-up, an estimation of the kinetics of the system, especially the diffusion, preferred reaction sites, and the rate of reaction of comproportionation – which has been to date unclear in the literature – was enabled. In this doctoral thesis, new analysis tools were used to improve the fundamental understanding of chemical and electrochemical reactions in organic RFBs. By understanding degradation processes, aggregation, and interfacial processes, we are able to provide information for designing electrolytes more effectively, working with optimised parameters, such as pH and supporting electrolyte concentration, and provide valuable insight into the electrode structures and their reaction centres.Item Embargo Synthesis and Optical Characterisation of Diphenylhexatriene Derived Intramolecular Singlet Fission MaterialsMillington, Oliver; Millington, Oliver [0000-0001-6787-8553]There is strong motivation for the detailed exploration of physical processes that present the potential for enhancing the power conversion efficiencies of solar photovoltaic devices. One key assumption underlying the theoretical Shockley-Queisser limit of the efficiency of photovoltaic devices is that the absorption of one photon can only produce a single electron-hole pair; all excess energy above the bandgap of the semiconductor is lost to thermalisation. Singlet fission (SF) is a physical process in certain organic materials that enables the production of two excited states, each with triplet multiplicity, from a lone photoexcited singlet state. It has been widely recognised that integration of an appropriately energetic and efficient singlet fission material into a photovoltaic device may facilitate circumvention of the Shockley-Queisser efficiency limit. This requires that the energy of both SF-born triplets can be harvested independently and transferred to the semiconductor. In covalently connected assemblies of a singlet fission active chromophore, intramolecular singlet fission (iSF) can generate two triplet states upon a single molecule. The singlet fission properties of the molecule can be tailored by synthetic engineering of the interchromophore connectivity. Only a modest sub-set of the chromophores that have been identified to undergo SF in condensed phases have been investigated in molecular systems for iSF activity. 1,6-Diphenylhexa-1,3,5-triene (DPH) is a promising chromophore that is known to undergo singlet fission in the solid state. The high triplet energy of DPH (~ 1.5 eV) makes it a particularly attractive chromophore for further studies, given the identification of high triplet energy as a critical requirement for the viable application of SF in photovoltaic systems. In the work described in this thesis, the first studies of iSF activity in DPH materials were conducted. This thesis describes the design and chemical synthesis of the initial dimeric DPH derivatives for investigation as iSF candidates. The optical characterisation of these materials using transient absorption spectroscopy is reported and two of the initial five materials are found to form an ultrafast equilibrium between singlet and triplet-pair states. Following the initial studies, several subsequent generations of DPH dimers and oligomers are investigated. Facile iSF to generate a triplet-pair state is achieved for several materials but reducing triplet-pair annihilation, in order to achieve persistent pairs of triplets, proves elusive. Nevertheless, significant progress is achieved with the formation of spatially separated triplet-pairs being identified for contiguously connected oligomers, presented in the final chapter. Stabilisation of these spatially separated triplet populations remains the outstanding challenge for the generation of persistent pairs of triplets.Item Embargo Utilising Non-Covalent Interactions in Developing Enantioselective Radical TransformationsBacos, Paul DavidThis thesis details the development of catalytic, enantioselective strategies for radical reactions, utilising non-covalent interactions to control the asymmetry of these processes. The first research chapter describes the use of chiral phosphoric acids to control the enantioselectivity in the reactions of α-amino radicals. Firstly, a Giese reaction with α,β-unsaturated carbonyls is reported. This was found to be successful for a range of substrates, with the catalyst being able to exert control over the stereocentres originating from both the amine nucleophile and the acrylamide acceptor. Secondly, a reaction with polarity-mismatched acceptors, in the form of electron-rich enamides, is disclosed. While high enantioselectivities were achieved in some cases, the reaction was found to be effective only for a limited range of substrates. Thirdly, the Minisci-type addition of cyclic α-amino radicals into heteroarenes is detailed, including substrate design and limitations of the process. The second research chapter details preliminary studies into developing asymmetric nickel-catalysed functionalisations of α-amino radicals, using two different approaches. Initially, investigations were performed to determine whether chiral phosphoric acids, bound to the substrate via hydrogen bonding, could induce asymmetry. The subsequent approach relied on using an anionic ligand, ion-paired to a chiral cation derived from cinchona alkaloids, to create a chiral environment around the metal centre. The challenges encountered for both approaches are discussed. The third research chapter describes the incipient phase of a project based on the use of cinchona alkaloids-derived catalysts to perform enantioselective and desymmetrising hydrogen atom transfer from vicinal diols. The α-hydroxy radicals generated in the process were utilised in Giese additions and stereochemical isomerisation reactions, with high levels of enantioselectivity.Item Embargo Carbon dots as sustainable photocatalysts for organic synthesisLage, AvaAs easily scalable, cost-effective and environmentally benign materials, carbon dots (CDs) have the potential to replace costly or harmful photocatalysts for a range of synthetically relevant transformations. This dissertation aims to establish CDs as versatile, sustainable photocatalysts for organic synthesis. Chapter 2 explores CDs as photocatalysts for net-oxidative and redox-neutral C-C bond formation. A variety of aromatic substrates and biological motifs were successfully trifluoromethylated under aerobic conditions. To utilise the full potential of this reaction, the net-oxidative trifluoromethylation was coupled to H2-evolution, thereby generating two products simultaneously: a trifluoromethylated aryl and feedstock for hydrogenation. Chapter 3 subsequently introduces CDs as photocatalysts for net-reductive reactions by example of dehalogenation of aryl-iodides, -bromides and -chlorides. The C-halogen bond was successfully cleaved for all three substrate groups despite the strong reduction potential required particularly for the bromides and chlorides. As the CD reduction potential, while appreciable, is not sufficient to drive some of these reactions, mechanistic studies were undertaken to illuminate possible reaction pathways. Chapter 4 expands the application of CDs to C-C bond formation reactions that are currently difficult to access without transition metal catalysts or under visible light irradiation. The examples in this chapter include cross-coupling of 1,4-Dicyanobenzene with aldehydes and ketones as well as pinacol coupling of aldehydes and ketones. Chapter 5 branches out to dual catalytic systems by using CDs in combination with a Ni-catalyst to perform cross-couplings to achieve C-O and C-N bond formation. Additionally, photoluminescence quenching and transient absorption studies were undertaken to further examine the interaction between the CDs and Ni-catalyst, as well as gain insight into the CD states involved in the reaction. The data suggests the possible involvement of an energy transfer pathway, which would be the first example of CDs as an energy transfer catalyst in organic photocatalysis.Item Open Access Investigating the atmospheric composition and climate response to mitigation: a methane emissions-driven approachStaniaszek, Zofia; Staniaszek, Zofia [0000-0002-1789-4368]Methane is the second most important greenhouse gas after carbon dioxide, and also plays a central role in the chemistry of the atmosphere. The combination of its shorter lifetime and higher effectiveness as a greenhouse gas makes it an attractive option for near-term mitigation of climate change. Methane is also a key tropospheric ozone precursor: ozone is a greenhouse gas, and acts as an air pollutant in the troposphere. Therefore, mitigation of methane has both climate and air quality benefits. A new configuration of the UK Earth System Model, UKESM1-ems, has been developed with an updated methane treatment. Methane emissions are input directly, rather than prescribing a global surface concentration. This thesis focuses on UKESM1-ems and the new capabilities it provides: a more process-based treatment of methane; simulating feedbacks in the methane cycle, and the ability to directly perturb methane emissions. When compared to the previous, concentration-driven model, UKESM1-ems simulates the methane distribution with a better correlation compared to observations, including an improved latitudinal distribution, interhemispheric gradient and vertical gradient. The observed trend in methane over time is also reproduced, combining the methane emissions inputs, online wetland emissions and online chemistry and transport to simulate the methane mixing ratio. The modelled absolute methane mixing ratio is lower than observations: this is likely due to an underestimate in methane emissions, within the current large uncertainty range for emissions. Experiments following different emissions pathways are explored using UKESM1-ems. Firstly, an idealised scenario where all anthropogenic methane emissions are removed instantaneously, to attribute the role of future anthropogenic methane. Methane declines to below pre-industrial levels within 12 years and global surface ozone decreases to levels seen in the 1970s. By 2050, 690,000 premature deaths per year and 1 degree of warming can be attributed to anthropogenic methane. Secondly, the same low-methane scenario is used, with perturbed nitrogen oxide (NOx) and carbon monoxide (CO) emissions, to investigate their impact on the atmospheric oxidising capacity and test the hydroxyl (OH) relationship to NOx and CO. The effect of methane on NOx is also explored. Decreased methane emissions perturb both the NO/NO2 ratio and the partitioning between NOx and reservoir species, leading to increased NOx in low-methane scenarios. Finally, a Global Methane Pledge scenario is simulated. This pledge aims to reduce methane emissions by 30% globally by 2030, compared to 2020 values. The new ability of UKESM1-ems to mask emissions from different countries is used to implement this scenario and study regional impacts. The global mean methane mixing ratio decreases by 13% compared to 2020 levels. The expected temperature benefit (0.2°C) following this scenario is not seen in this experiment - this signal is too small and is within the noise and interannual variability of UKESM1-ems. There are global benefits for air quality, with ozone concentrations and population exposure to ozone decreasing in all countries. Global Methane Pledge member countries, where emissions reductions take place, see greater local air quality benefits than non-member countries.Item Embargo Developments in White Pigment Production Using Biocompatible Cellulose-Based MaterialsZhang, YatingWhite pigments are widely used in various everyday products, including paints, food, and cosmetics. The primary choice for achieving white colouration in industries has traditionally been high refractive index inorganic materials, notably titanium dioxide (TiO2), which recently has raised significant concerns among consumers. Consequently, there is a growing need to explore safer and more biocompatible alternatives. Over the last few years, cellulose-based materials have gained interest in different industrial sectors as well as in fundamental research, basically due to its abundance, biocompatibility, biodegradability, and environmental friendliness. This thesis presents the development of three distinct methods for producing white pigments using cellulose-based nanomaterials. Firstly, an inkjet printing method based on the evaporation-induced phase separation of ethyl cellulose (EC) was developed. The resulting porous films demonstrate enhanced reflectance compared to TiO2 formulations with equivalent solid content. The inherent biocompatibility of cellulose materials, in conjunction with the simplicity and versatility of inkjet printing, renders this approach highly promising for advanced white colouration production in the printing industry. Secondly, a scalable and straightforward spray-freeze-drying method using natural cellulose nanofibrils (CNFs) was introduced. This approach enables the production of ultra-light and highly porous cellulose aerogel microparticles, thereby opening up the possibility of using natural cellulose material for white pigment particle production. Lastly, a novel method termed as "organic solvent mixing" was developed using cellulose microparticles (CMPs) with optimised scattering dimensions. This proposed method combines the concepts of evaporation-induced phase separation and solvent exchange to address the issue of densification upon water drying. The method successfully yields films with optical properties comparable to those obtained through previously complex techniques. Moreover, this method offers notable advantages, including ease of operation, straightforward implementation, reduced toxicity, and lower cost.Item Embargo Understanding the Limits of Lithium-Air Batteries – NMR and Thermodynamic StudiesEllison, James; Ellison, James [0000-0002-4578-5804]Lithium-air batteries promise to deliver exceptionally high energy density while only using common materials, such as carbon, in their cathode structure. To do this, they oxidise a metallic lithium anode to release Li+ ions, which combine with O22- ions, produced from the reduction of atmospheric oxygen. However, such batteries are yet to be commercialised due to problems in cell operation, such as their high overpotentials, poor rate capabilities and, most critically, poor cell lifetimes. This work sets out to quantify the realistic expectations that should be had of a lithium-air battery should they be realised and the cell geometry and support systems such a battery would likely need. It goes on to discuss the theory of the chemical structural motifs that promising new solvents would likely have. To aid in studying the breakdown products formed in the lithium air batteries, which limit their lifetime, operando 17O nuclear magnetic resonance was developed. This technique can non-destructively and in real time track and quantify the formation and removal of all common breakdown products, this information challenging to access by any other technique. Operando diffraction can in principle access it, however it typically requires a synchrotron and if often limits to crystalline products. Operando Raman is typically surface sensitive and chemical tests are destructive. Here 17O NMR is used to investigate the relative contributions of singlet oxygen, chemical and electrochemical breakdown to the observed decomposition products in the cell. To support this work Gaussian Process regression was utilized. It was found that Gaussian processes can also be used to denoise NMR data, matching or outperforming current denoising methods in many cases. Finally, a potential additive to the electrolyte, lithium iodide, is discussed. Lithium iodide had previously been proposed to reduce the charge overpotential and switch the discharge product in the battery to LiOH, thereby avoiding many of the corrosive species formed in the cell. Here, the thermodynamics and kinetics associated with this reaction are explored, and the range of conditions where this reaction is possible is discussed.