The binding of tyrosine phosphorylated targets by SH2 domains is required for the propagation of many cellular signals in higher eukaryotes. In this thesis we studied computationally the bindings of Src SH2 domain to Ac-PQpYEpYIPI-NH2 and Ac- PQpYIpYVPI-NH2, two dually-phosphorylated ligands, and their interfacial water molecules. Structures of SH2 domains with bound ligands indicate a potentially important role of water in influencing binding thermodynamics. We have investigated the role of interfacial water molecules on the prediction of the thermodynamics of SH2 domain "" binding to phosphopeptides using a method based on accessible surface area buried upon association. We show that the model does not predict the binding thermodynamics of either ligand. However, we identified the empirical formula describing the heat capacity change values as falling from 0 to -300 cal/mol.deg results in a sharp distribution of the number of ligandlSH2/water-subset structures that provide binding thermodynamics similar to experimental values. This prompted us to experimentally determine the heat capacity change for each of the peptides and we found them to coincide with the values of the peaks. We next used molecular dynamics (MD) simulation methods to evaluate solvation sites at the binding interface of the Src SH2 domain. We showed that the method computed the first water shell of the protein and predicted the crystallographic water molecules positions at 50 to 80% within a distance of 0.9 angstroms, on average. Comparison of the simulated water structures of both the bound and unbound binding partners led to a thorough evaluation of water behaviour during the binding reaction. We also showed that the simulated water structures of all ligandlSH21 domain structures investigated here can be used to accurately derive the binding heat capacity change using a method based on accessible surface area buried upon association. Finally, we studied the interfacial solvation energetic landscapeof structures of the Src SH2 domain bound to three dually phosphorylated ligands, and investigated the difference in the energetic landscape of the bound complexes. We have found that the energy change in the thermodynamic signature difference between Ac-PQpYEpYIPI-NH2 and Ac-PQpYlpYVPI-NH2 binding is due to the combination of small structural rearrangements in the position of protein's and ligand's residues resulting in a higher flexibility of the +2 phosphotyrosine. The insights gained into the binding event from these simulation experiments lead to a better understanding of the role of water in influencing the binding thermodynamics.

We report here the design, purification and structural characterization of a new protein scaffold for cell culture. Prior studies in our group revealed the structure of the bacterial protein Caf1 to be flexible protein nanofibres, up to 1.5 μm. The existing Cafl expression system was cumbersome and difficult to mutate, we have now produced a system containing the caf operon which allows for the incorporation of specific peptide motifs. The small peptide, RGDS from fibronectin was inserted into 5 different surface loops of Caf1. The Caf1 mutants were expressed and purified and a structural characterization by biophysical methods was conducted. This revealed permissive sites into which new motifs can be inserted. The characterised proteins were sterilised and used to coat 96 well plates for cell culture. In this study we used mammalian cell lines such as 3T3 fibroblasts, PC12 neuronal cells and primary osteoblasts to understand how they behave in the presence of this biomaterial, in particular the formation of focal adhesions, changes in cytoskeleton rearrangement and nuclear and cell morphology. The controlled engineering of sites within the polymer allowed us to study their implication in cell attachment, survival and proliferation. Our preliminary results have shown that cells interact poorly with the unmodified protein e.g. without any motif associated. This reveals that the polymer is inert and does not influence cell growth by itself. In contrast, the incorporation of RGDS, can invert the scenario of cell growth; promoting cell attachment, survival and proliferation. In a second stage of the project we designed a separate compatible plasmid encoding caf1 gene and used it with the previous plasmid to co-express hybrid Caf1 polymers. The long fibres can also be crosslinked with a non-toxic and non-immunogenic chemical compound – NHS-PEG. Thus a protein hydrogel composed of interchangeable folding units which can be used to incorporate different cell interacting peptide motifs. It is robust and, in the unmodified state highly protease resistant. Future studies will elucidate the versatility and potentiality for this peptide hydrogel in stem cell differentiation.

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The classification of protein structures into evolutionary superfamilies, for example in the CATH or SCOP domain structure databases, although performed with varying degrees of automation, has remained a largely subjective activity guided by expert knowledge. The huge expansion of the Protein Structure Databank (PDB), partly due to the structural genomics initiatives, has posed significant challenges to maintaining the coverage of these structural classification resources. This is because the high degree of manual assessment currently involved has affected their ability to keep pace with high throughput structure determination. This thesis presents an evaluation of different methods used in remote homologue detection which was performed to identify the most powerful approaches currently available. The design and implementation of new protocols suitable for remote homologue detection was informed by an analysis of the extent to which different homologous superfamilies in CATH evolve in sequence, structure and function and characterisation of the mechanisms by which this occurs. This analysis revealed that relatives in some highly populated CATH superfamilies have diverged considerably in their structures. In diverse relatives, significant variations are observed in the secondary structure embellishments decorating the common structural core for the superfamily. There are also differences in the packing angles between secondary structures. Information on the variability observed in CATH superfamilies is collated in an established web resource the Dictionary of Homologous Superfamilies, which has been expanded and improved in a number of ways. A new structural comparison algorithm, CATHEDRAL, is described. This was developed to cope with the structural variation observed across CATH superfamilies and to improve the automatic recognition of domain boundaries in multidomain structures. CATHEDRAL combines both secondary structure matching and accurate residue alignment in an iterative protocol for determining the location of previously observed folds in novel multi-domain structures. A rigorous benchmarking protocol is also described that assesses the performance of CATHEDRAL against other leading structural comparison methods. The optimisation and benchmarking of several other methods for detecting homology are subsequently presented. These include methods which exploit Hidden Markov Models (HMMs) to detect sequence similarity and methods that attempt to assess functional similarity. Finally an automated, machine learning approach to detecting homologous relationships between proteins is presented which combines information on sequence, structure and functional similarity. This was able to identify over 85% of the homologous relationships in the CATH classification at a 5% error rate. This thesis was gratefully supported by the Biotechnology and Biological Sciences Research Council.

Over the last few years it has been shown that protein modelling techniques, especially template based modelling, are now accurate enough for qualitative analysis and decision-making in support of a wide range of experimental work. Automatic protein modelling pipelines are becoming ever more accurate; however, this has come hand in hand with an increasingly complicated interplay between all components involved. Despite all progress, still important problems remain and so far computational methods cannot routinely meet the accuracy of experimentally determined protein structures. In protein modelling pipelines, several important steps dictate a model's quality. Selecting a good template and aligning the query sequence correctly, backbone completion, model refinement and final model selection are considered the main steps. As a first step to approach protein refinement, a genetic algorithm (GA) for protein model recombination and optimization is presented in this work. This algorithm has the potential, to drive models away from the template towards the native structure. Furthermore, a complete and novel modelling pipeline, incorporating this GA is presented. In this context, a new scoring scheme, backbone repair algorithm and several other findings are reported and presented: We introduce the novel concept of Alternating Evolutionary Pressure, i.e. intermediate rounds within the GA simulation, where unrestrained linear growth of the model population is allowed. This approach improves the structural sampling and thereby facilitates energy-based model selection. Finally, the GA in combination with molecular dynamics simulations is used in the context of protein engineering. Several mutants were identified to stabilise and increase the activity of the cancer drug L-Asparaginase, a complex enzyme. The successful prediction of these mutations stresses the importance of protein molecular modelling for cell biology and in a clinical context.