Cell separation based on antibody-targeted magnetic beads has been widely used in a number of applications in immunology, microbiology, oncology and more recently, in the isolation of circulating tumour cells (CTCs) in cancer patients. Although other cell separation techniques such as size based cell filtration and Fluorescence Activated Cell Sorting have also been in popular use, immunomagnetic cell isolation possesses the advantages of high throughput, good specificity and reduced cell stress. However, certain fundamental features of the cell-bead interface are still unknown. In this study, some of the key features of the cell-bead synapse were investigated in an effort to improve the efficiency of immunomagnetic cell isolation and reduce its dependence on high expressing cell surface markers. A clinically relevant antibody fragment (Fab) against tyrosine kinase receptor HER2 was applied to study the immunomagnetic isolation of HER2 expressing cancer cells. First, the minimum number of target proteins required on a cell for it to be isolated was determined. Second, the importance of the primary antibody affinity was investigated, using a series of Fab mutants with known kinetics and it was shown that despite starting with sub-nanomolar affinity, improving Fab affinity increased cell isolation. Third, the influence of the connection between the primary antibody and the bead was studied by comparing Fab bridged to the magnetic bead via a secondary antibody, Protein L or streptavidin; the high affinity biotin-streptavidin linkage increased isolation sensitivity by an order of magnitude. Fourth, the effect of manipulating cytoskeletal polymerization and cell membrane fluidity using small molecules was tested; cholesterol depletion decreased isolation and cholesterol loading increased cell isolation. The insights from these observations were then applied to isolate a panel of cell lines expressing a wide range of surface HER2. While the standard approach isolated less than 10% of low HER2 expressing cancer cells from spiked rabbit and human blood, our enhanced approach with the optimized cholesterol level, antibody affinity and antibody-bead linkage could specifically isolate more than 80% of such cells. The final part of this work focussed on developing an antibody clamp that could physically restrict the antigen within its binding site on the Fab and prevent antigen dissociation, using the HER2-Fab complex and the anti-myc peptide antibody 9E10. Work from this thesis provides useful insights into the molecular and cellular parameters guiding immunomagnetic cell isolation and can be used to extend the range of target receptors and biomarkers for tumour cell isolation and other types of cell separation, thereby enhancing the power and capacity of this approach.

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Proteins and their intricate network of interactions are fundamental to many molecular processes that govern life. Mass spectrometry-based structural proteomics represents a powerful set of techniques for characterizing protein structures and interactions. The last decade has witnessed a large-scale adoption in the application of these techniques toward solving a variety of biological questions. Addressing these questions has often been coincident with the further development of these techniques. Insight into the structures of individual proteins and their interactions with other proteins in a proteome-wide context has been made possible by recent developments in the relatively new field of chemical crosslinking combined with mass spectrometry. In these experiments crosslinking reagents are used to capture protein-protein interactions by forming covalent linkages between proximal amino acid residues. The crosslinked proteins are then enzymatically digested into peptides, and the covalently-coupled crosslinked peptides are identified by mass spectrometry. These identified crosslinked peptides thus provide evidence of interacting regions within or between proteins. In this dissertation the development of tools and methods that facilitate this powerful technique are described. The primary arc of this work follows the development and application of mass spectrometry-based approaches for the identification of protein crosslinks ranging from those which exist endogenously to those which are introduced synthetically. Firstly, the development of a novel strategy for comprehensive determination of naturally occurring protein crosslinks in the form of disulfide bonds is described. Secondly, the application of crosslinking reagents to create synthetic crosslinks in proteins coupled with molecular dynamics simulations is explored in order to structurally characterize the intrinsically disordered tau protein. Thirdly, improvements to a crosslinking-mass spectrometry method for defining a protein-protein interactome in a complex sample is developed. Altogether, these described approaches represent a toolset to allow researchers to access information about protein structure and interactions. / Graduate

The Protein Data Bank (PDB) is the definitive electronic repository for experimentally-derived protein structures, composed mainly of those determined by X-ray crystallography. Approximately 200 new structures are added weekly to the PDB, and at the time of writing, it contains approximately 97,000 structures. This represents an expanding wealth of high-quality information but there seem to be few bioinformatics tools that consider and analyse these data as an ensemble. This thesis explores the development of three efficient, fast algorithms and software implementations to study protein structure using the entire PDB. The first project is a crystal-form matching tool that takes a unit cell and quickly (< 1 second) retrieves the most related matches from the PDB. The unit cell matches are combined with sequence alignments using a novel Family Clustering Algorithm to display the results in a user-friendly way. The software tool, Nearest-cell, has been incorporated into the X-ray data collection pipeline at the Diamond Light Source, and is also available as a public web service. The bulk of the thesis is devoted to the study and prediction of protein disorder. Initially, trying to update and extend an existing predictor, RONN, the limitations of the method were exposed and a novel predictor (called MoreRONN) was developed that incorporates a novel sequence-based clustering approach to disorder data inferred from the PDB and DisProt. MoreRONN is now clearly the best-in-class disorder predictor and will soon be offered as a public web service. The third project explores the development of a clustering algorithm for protein structural fragments that can work on the scale of the whole PDB. While protein structures have long been clustered into loose families, there has to date been no comprehensive analytical clustering of short (~6 residue) fragments. A novel fragment clustering tool was built that is now leading to a public database of fragment families and representative structural fragments that should prove extremely helpful for both basic understanding and experimentation. Together, these three projects exemplify how cutting-edge computational approaches applied to extensive protein structure libraries can provide user-friendly tools that address critical everyday issues for structural biologists.

As depicted in Chapter I, 2-oxoglutarate- (2OG) dependent oxygenases are ubiquitous in living systems and display a wide range of cellular functions, spanning metabolism, transcription, and translation. Although functionally diverse, the 2OG oxygenases share a high degree of structural similarities between their catalytic sites. From a medicinal chemistry point of view, the combination of biological diversity and structural similarity presents a rather challenging task for the development of selective small molecules for functional studies in vivo. The non-selective metal chelator 8-hydroxyquinoline (8HQ) was used as a template for the generation of tool compound <b>I</b> for the KDM4 subfamily of histone demethylases via application of the Betti reaction. Structural analogue <b>II</b> was used as the corresponding negative control (Figure A). These compounds were characterised in vitro against a range of 2OG oxygenases and subsequently used for studies in cells. <b>I</b> displays selectivity for KDM4 and increases the level of the H3K9me3 histone mark in cells. It has an effect on the post-translational modification pattern of histone H3, but not other histones, and reduces the viability of lung cancer cells, but not normal lung cells, derived from the same patient. <b>I</b> also stabilises hypoxia-inducable factor HIF in cells via a mechanism which seems to be independent from prolyl hydroxylase inhibition. This work is described in Chapters II and III. The chemical biology research in epigenetics is complemented by qualitative analysis conducted in the social sciences at Said Business School. With a global view on how innovation occurs and may actively be fostered, Chapter IV focuses on the potential of epigenetics in drug discovery and how this process may actively be promoted within the framework of open innovation. Areas of focus include considerations of incremental and disruptive technology; how to claim, demarcate, and control the market; how knowledge brokering occurs; and insights about process, management, organisation, and culture of open innovation. In contrast to the open-skies approach adopted for the development of a tool compound in Chapters II and III, a focused-library approach was taken for the generation of a tool compound for the OGFOD1 ribosomal prolyl hydroxylase. The development of a suitable in vitro activity assay for OGFOD1 in Chapter V enabled the development of lead compound <b>III</b> in Chapter VI. <b>III</b> is selective for OGFOD1 against the structurally closely related prolyl hydroxylase PHD2.