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.