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The function of a DNA sequence is commonly predicted by measuring its nucleotide similarity to known functional sets. However, the use of structural properties to identify patterns within families is justified by the discovery that many very different sequences have similar structural properties. The aim of this thesis is to develop tools that detect any unusual structural characteristics of a particular sequence or that identify DNA structure-activity fingerprints common to a set. This work uses the Octamer Database to describe DNA. The database's contents are split into two categories: those parameters that describe minimum energy structure and those that measure flexibility. Information from both of these categories has been combined to describe structural tendencies, offering an alternative measure of sequence similarity. A structural DNA profile gives a graphical illustration of how a parameter from the Octamer Database varies across either a single sequence's length or across a set of sequences. Profile Manager is an application that has been developed to automate single sequence profile generation and is used to study the A-tract phenomenon. The use of profiles to explore patterns in flexibility across a set of pre-aligned promoters is then investigated with interesting transitions in decreasing twist flexibility discovered. Multiple sequence queries are harder to solve than those of single sequences, due to the inherent need for the sequences to be aligned. It is only under rare circumstances that sequences are pre-aligned by an experimentally determined position. More commonly a multiple alignment must be generated. An extended, structure-based, hidden Markov model technique that successfully generates structural alignment~ is presented. Its. application is tested on four DNA protein binding site datasets with comparisons made to the traditional sequence method. Structural alignments of two out of the four datasets were comparable in performance to sequence with useful insights into underlying structural mechanisms.

The work described in this thesis is concerned with the development and application of the photo-CIDNP (Chemically Induced Dynamic Nuclear Polarization) technique to the study of native and non-native structures and folding pathways of polypeptides and proteins.

Most studies of membrane protein folding have focused on a-helical monomeric proteins. The next major challenge is to extend these folding studies to incorporate oligomeric membrane proteins, for which there is a paucity of information available on their folding and assembly. The folding of multisubunit proteins is a biologically important and far-reaching area of research since the majority of proteins exist as protein-protein complexes. In order to understand these proteins it is important to be able to recreate their folding and assembly in vitro starting with simple model protein complexes. Work in this thesis takes advantage of the modular organisation of BtuCD and methods are described to prepare the individual building blocks of the protein complex.

The scn1-1 mutants of Arabidopsis are characterised by spatially deregulated sites of root hair growth. This studydemonstrates that this phenotype is the result of the loss of regulation of members of the plant specific sub-family of Rho small GTPases by the Guanine nucleotide Dissociation Inhibitor (GDI), encoded by SCN1. The small GTPases R0P2, R0P4 and R0P5 of Arabidopsis are members of the I subset of type I ROPs that terminate with a conserved CXXL box and undergo 3 prenylation. These small GTPases are expressed in trichoblasts, and localize in patters suggestive of specific roles throughout root hair development. Loss-of function ROP2, R0P4 or ROP5 mutants display distinct root hair phenotypes lending support to the hypothesis that : R0P2, R0P4 and ROP5 control the establishment of the site of root hair initiation and subsequent tip-growth. Our findings also reveal SCNl/GDIl and R0P2 co-localize in a similiar pattern in developing root hairs in planta, but SCNl/GDIl is able to associate directly with ROP2, ROP4 and ROP5 in vitro.This suggests root hair morphogenesis relies on the negative regulation of ROP activity by SCNl/GDI 1 and is further supported by morphological phenotypes of scnl-l plants which can be rescued by the over expression of CFP:GD11 fusion placed under the control of the root hair specific PRP3 (Proline Rich Protein3) promoter. These observations imply that ROPs can be selectively sequestered away from the from plasma membrane of elongating root hairs during tip growth thereby promoting growth along a planar axis. Differences in the observed binding affinity of R0P2 in comparison to R0P4 and ROPS for SCNl/GDIl provides evidence that the CXXL box may play a critical role in ROP regulation, and that R0P2 and R0P4 are differentially prenylated.

Complexity science studies the dynamic interactions between components of a system. The sensitivity of these interactions to environmental conditions means that a single complex system expresses varying emergent behaviour; making its understanding difficult, particularly when it comes to predicting its behaviour. One such "complex" problem is protein folding, which addresses the question of how a linear sequence of amino acids carries information for a three-dimensional protein structure. Deciphering of a code, or even a subset of rules, that could accu- rately help predict the 3-dimensional arrangement of amino acids within a protein would be of tremendous benefit to the basic and applied chemical, biological and biomedical sciences. One approach to solving the protein folding problem is to learn to predict smaller structures and gradually increase the size of our targets. This Thesis follows a similar mindset and focusses on the coiled coil, a ubiquitous IX-helical protein- folding motif that is involved in many biological processes. Coiled-coil prediction can be separated into two distinct problems; firstly, the identification of coiled- coil regions within protein sequences; and, secondly, predicting the architecture and topology that a coiled-coil sequence is likely to adopt; i.e., its oligomer state and the orientation of its helices. The work presented in this Thesis is grounded on the application of statistical modelling to investigate both aspects of the coiled coil-prediction problem. First, a comprehensive assessment of the existing coiled-coil domain prediction algorithms is carried out and their limitations discussed. This forms the basis for the development of a coiled-coil domain meta-predictor, which shows improve- ments over the existing individual algorithms. The contributions of the work pre- sented in this Thesis regarding the prediction of coiled-coil topology are two-fold: firstly, SCORER 2.0, an algorithm that improves our ability to discriminate be- tween coiled-coil topologies, is introduced. Despite state-of-the-art performance, SCORER 2.0 and other existing predictors are limited to two-state predictions and cover only rv 33% of the known coiled-coil population. This triggered the devel- opment of LOGIC OIL, which is the major contribution of this Thesis. LOGICOIL is a Bayesian-based methodology that increases our ab initio prediction coverage of the known coiled-coil population from rv 33% to rv 93%, but also extends our ability to differentiate between multiple coiled-coil oligomeric states from amino- acid sequence alone. Finally, the usefulness of the prediction tools developed in this work is illustrated on problems of biological interest, more specifically on the prediction of coiled coils in the tenascin, thrombospondin and matrilin protein assemblies; i.e., proteins of the extracellular matrix. Here, the coiled-coil domain meta-predictor, and LOGICOIL are used to analyze the presence and structure of coiled-coils domains, as well as their contribution to the overall architecture of the protein complexes.

ADP ribosylation factors (ARFs) are a family of small GTPases from the ras superfamily. 6 members of the ARF family have been identified in mammals to date, with functions ranging from the regulation of vesicular coat protein assembly to the organisation of the actin cytoskeleton. ARFs have no intrinsic GDP/GTP exchange or GTPase activity, and so their GDP/GTP cycle is dependent on regulation by exchange factors and activating proteins.

ADP-ribosylation factors (Arfs) are a family of Ras-related, low molecular mass (~20kDa), GTP-binding proteins that are expressed in all eukaryotes. They regulate intracellular vesicular trafficking along secretory and endocytic pathways and play a role in actin cytoskeleton reorganisation. The Arf family in mammals consists of six Arfs (Arfl-6), fifteen Arf-like (Aril-16), Sari and TR1M23 proteins. A few years ago, using a proteomic approach, a novel Arf protein, Arl8b, was discovered. However, Arl8b is not well studied yet. In this thesis, the biochemical and cellular characterisation of Arl8b has been discussed.

Current genomic and proteomic research is generating a considerable number of potential new therapeutic targets. To tackle all these pharmacological targets, the development of rapid and reliable screening methods, which give information on protein-ligand interactions, are of great importance. New advances in these technologies are often emerging and more will surely follow.