Use this URL to cite or link to this record in EThOS:
Title: Exploring the fold space preferences of ancient and newborn protein superfamilies
Author: Edwards, Hannah Elizabeth
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2014
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
Protein evolution is a complex and diverse process, yielding an incredible assortment of biological functions and pathways occurring in the cells of living organisms. The way in which a protein's structure is constrained by its functional role and its notable conservation across even distant evolutionary relationships highlight structure as an important unit when considering the evolutionary dynamics of proteins. This thesis attempts to place the structural landscape of the protein universe within an evolutionary framework. We investigate potential evolutionary histories of protein superfamilies by introducing an age, which estimates when the ancestor of that superfamily first evolved. The range of ages of known protein superfamilies goes right back to those which evolved before the diversification of life into three major superkingdoms. The structures of these proteins are varied but those which have evolved more recently tend to be shorter and have a less elaborate globular packing. Protein structures sit within a complex global landscape of three-dimensional folds and we attempt to model the dynamics of this space using networks of folds. These networks consist of a structurally diverse core of folds with older ages, and neighbouring folds tend to be of similar ages. Moreover, there are a few pivotal folds which appear repeatedly as central in the landscapes, connecting together otherwise disparate portions of the space. Sequence profiles which capture patterns of conservation and variation amongst naturally occurring proteins within a superfamily can be compared to identify distant evolutionary relationships. The power of these profiles to detect such relationships is improved by seeding them with structural alignments. A landscape of evolutionary links crossing between different protein folds is presented.
Supervisor: Deane, Charlotte M. Sponsor: Engineering and Physical Sciences Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Mathematical genetics and bioinformatics (statistics) ; Protein folding ; Mathematical biology ; Life Sciences ; Bioinformatics (life sciences) ; protein structure ; fold space ; protein evolution ; protein structure classification