Post-genomic biomedical science requires quantitative proteomics. In most cases this involves differential protein expression analysis using matched pairs of simultaneously detectable labelling reagents for specific protein amino acids. In this thesis the development and optimisation of a novel cysteine labelling strategy, that is based on the use of iodoacetyl derivatives of Cy3 and Cy5 (ICy3/5) and 2D-difference gel electrophoresis (2D-DIGE) is described. The differentially labelled samples are separated on a single 2D gel and detected by multi-wavelength fluorescence scanning. The method is used to analyse standard proteins and then cell lysates to define the stoichiometry, sensitivity and specificity of this labelling technique. A comparative study of this new proteomic ICy dye protocol with the current NHS-Cy dye labelling system and methods that employ commonly used protein staining methods is described. The method is then used for cysteine labelling of proteins in non-reduced, denatured biological samples allowing accurate monitoring and sensitive detection of redox-dependent thiol modifications and expression level changes. The method is shown to be compatible with the use of MALDI mass spectrometry to identify proteins by analysis of trypsinised ICy labelled peptide digests. Using parallel sample analysis within single gels, the ICy-dye reagents were used to detect redox-, ErbB-2- and growth factor-dependent changes in a human mammary luminal epithelial cell system which was exposed to hydrogen peroxide or to growth factor stimulation. The conventional lysine labelling 2D-DIGE technique was also used in parallel to assess the new ICy labelling strategy for determination of the effects of oxidative stress on protein isoform levels. This study has revealed the identity of proteins involved in the response to oxidative stress and growth factor stimulation in the context of ErbB-2 growth factor receptor over-expression. In addition, this labelling strategy was also used to detect changes in thiol reactivity that follow the UV irradiation of plasma proteins as part of a study designed to evaluate the effect of UV disinfection on plasma product safety for clinical use.

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Proteins are frequently composed of multiple domains which fold independently. These are often evolutionarily distinct units which can be adapted and reused in other proteins. The classification of protein domains into evolutionary families facilitates the study of their evolution and function. In this thesis such classifications are used firstly to examine methods for identifying evolutionary relationships (homology) between protein domains. Secondly a specific approach for predicting their function is developed. Lastly they are used in studying the evolution of protein complexes. Tools for identifying evolutionary relationships between proteins are central to computational biology. They aid in classifying families of proteins, giving clues about the function of proteins and the study of molecular evolution. The first chapter of this thesis concerns the effectiveness of cutting edge methods in identifying evolutionary relationships between protein domains. The identification of evolutionary relationships between proteins can give clues as to their function. The second chapter of this thesis concerns the development of a method to identify proteins involved in the same biological process. This method is based on the concept of domain fusion whereby pairs of proteins from one organism with a concerted function are sometimes found fused into single proteins in a different organism. Using protein domain classifications it is possible to identify these relationships. Most proteins do not act in isolation but carry out their function by binding to other proteins in complexes; little is understood about the evolution of such complexes. In the third chapter of this thesis the evolution of complexes is examined in two representative model organisms using protein domain families. In this work, protein domain superfamilies allow distantly related parts of complexes to be identified in order to determine how homologous units are reused.

The antiquity of handaxes was first noted over 200 years ago (Frere, 1800) and since then archaeologists have attempted to categorise and explain them. We are now much closer to elucidating the answers to why and how they were made, what they were used for and what they signify about past hominin behaviour. In a British context, several authors have contributed significant leaps forward in the comprehension of these processes, most notably, Roe (1968), Wymer (1968) and more recently McPherron (1995), White (1998a) and Ashton (2003). The work pioneered by Roe (1968) emphasised the variability present within handaxe-dominated assemblages from the British Palaeolithic and attempted to place this variation within an objective typological framework. Subsequent authors have utilised Roe’s methodology to attempt to ascertain the basis for this metrical variability both within and between handaxe-dominated assemblages, positing causal factors such as raw material (Ashton and McNabb, 1994; White, 1998a), resharpening (McPherron, 1995) and cultural design (Wenban-Smith, 2004). This study examines the basis and methodology of these hypotheses through the technological analysis of twenty two British Palaeolithic localities. The focus of this examination is Roe’s decision to divide assemblages into Point, Ovate and Cleaver Traditions, groupings which have become the standard through which to understand and classify handaxe variability within Britain. The results of this analysis indicate that resharpening is a key factor in determining handaxe shape and that metrical classification alone can never deliver us the types of tool-specific information necessary to make sense of observed patterning in the archaeological record. This suggests that it is perhaps time to move towards a new analytical framework for handaxes, one in which the fluidity of form during handaxe use-life (Shott, 1989) is taken into account. Moving beyond Roe’s (1968) paradigm will allow us to engage with the processes and rhythms of the Lower and Middle Palaeolithic chaîne opératoire in a way simply unavailable through metrical classification.

Protein-ligand interactions are central to many biological processes. Developing a detailed understanding of protein-ligard interactions is therefore fundamental to the molecular life sciences. This study aims to further our understanding of how structure relates to the thermodynamics of binding. By constructing a database (SCORPIO) of calorimetric and structural data on the interactions of proteins with both biological ligands and synthetic inhibitors, we have created a resource which enables analysis and hypothesis testing of structure-thermodynamic correlations. The data in SCORPIO have been used to identity differences in the thermodynamics of binding of native ligands and synthetic inhibitors. The SCORPIO data have also been used to show that enthalpy-entropy compensation is a real phenomenon and not just an artefact of a limited affinity window. By-analysing the changes in surface area upon protein-ligand complexation, buried apolar surface is found to correlate well with ΔG (change in free energy) (R^2=0.65). Contrary-to common belief, this relationship cannot be simply explained by an underlying correlation with ΔS (change in entropy). The surface area analysis has some inherent weaknesses in that complementarity is assumed and water-mediated interactions are ignored. An atom-atom contact approach that explicitly deals with waters has therefore been developed and tested. Using the atom-atom contact approach a multiple linear regression (MLR) model describing ΔG has been created. The descriptors selected reflect the changes in polar- and apolar- hydration upon forming the complex. Interestingly direct contacts between the protein and the ligand do not appear to be important for describing the variance in ΔG, although some results indicate that the polar atom-atom contact descriptor is not sensitive enough to be used as a predictor of ΔG in the MLR model.

The prediction of protein secondary and tertiary structure is becoming increasingly important as the number of sequences available to the biological community far exceeds the number of unique native structures. The following chapters describe the conception, construction, evaluation and application of a series of algorithms for the prediction and evaluation of two and three-dimensional protein structure. In chapter 1 a brief overview of protein structure and the resources required to predict protein features is given. Chapter 2 describes the investigation of sequence identity and alignments on the prediction of two-dimensional protein structure in the form of long and short range protein contacts a feature which is known to correlate with solvent accessibility. It also describes the identification of a feature which is referred to as the 'Empty Quarter' which forms the basis of an evaluation function described in Chapter 3 and developed in Chapter 4. Chapter 3 introduces the Dynamic Domain Threading method used during round six of the CASP exercise. Phobic, a protein evaluation function based on predicted solvent accessibility is described in Chapter 4. The de novo prediction of a/p proteins is described in Chapter 5, the method introduces a new approach to the old problem of combinatorial modelling and breaks the size limit previously imposed on de novo prediction. The final experimental chapter describes the prediction of solvent accessibility and secondary structure using a novel combination of the fuzzy k-nearest neighbour and support vector machine. Chapter 7 closes this piece of work with a review of the field and suggests potential improvements to the way work is conducted.

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