Sykes_whole_thesis.pdf (11.6 MB)
Protein structure and evolution
thesis
posted on 2023-05-28, 11:59 authored by Sykes, JEProteins are a major interface between the genotype and phenotype of living things. Understanding the structure of these molecules, and how their structure interacts with their sequence and function, is vital to our knowledge of all life. Specifically, knowledge of protein structure evolution has a multitude of applications in health and biology, as it could allow us to accurately predict the effects of any protein mutation and use this knowledge for drug discovery and to combat disease. Protein structural relationships and changes can be effectively mapped using a network, with the proteins represented as nodes and connections between them indicating degree of similarity or possible evolutionary relationships. Many different approaches to determining where these connections should lie have been presented, with all producing complex pictures of the protein universe. However, constructing a model of protein structural change that captures enough physical and chemical information to make accurate predictions remains a major challenge. With this ultimate goal in mind, I present three original studies that contribute to our understanding of protein structure. The first is a benchmarking study of protein structure alignment methods, with efficacy assessed through their ability to determine levels of structural similarity between protein domains and to cluster domains into those of equivalent structure. Sorting proteins by structure is relevant to many biochemical problems, including constructing networks based on structural similarity. The second study assesses the completeness of our current understanding of protein structure space by focusing on triplets of secondary structure elements. Determining whether or not the current Protein Data Bank (PDB) contains all structures of proteins will give an idea of the level of novelty we can expect in a complete network of protein evolution. The third study looks at the relationships between contact density, protein age and protein sequence diversity. These are all potential contributors to determining possible evolutionary links between proteins. Also, relationships between these variables could result in patterns of similarity in networks that could otherwise be explained through convergent or divergent evolution. It is our hope that the results of this work will inform future network-based representations of the protein universe.
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