At present, the most accurate approach to predicting protein structure, comparative modelling, builds a model of a target sequence using known protein structures as templates. Comparative modelling becomes markedly less accurate in the ‘twilight zone’, where the target protein shares little sequence identity with all known templates. There are two main causes of this inaccuracy: first, it becomes difficult to identify good structural templates; second, it becomes difficult to determine which amino acids in the template are structurally equivalent to those in the target. These are problems of fold recognition and target-template alignment respectively. In this thesis, new approaches are developed to address both these problems. The alignment problem is investigated in the special case of membrane proteins. These are key modelling targets as they resist structure determination and are pharmaceutically important. The approach taken here is to use ‘environment specific substitution tables’ (ESSTs)– that is, to alter the alignment scoring system for each local environment of the template structure. We show how ESSTs can be made for membrane proteins, tested for robustness of construction, and used to infer the most important evolutionary pressures acting on protein structure. The incorporation of ESSTs into a multiple sequence alignment method leads to more accurate alignments of membrane proteins, and so to more accurate models. Recently, algorithms have been developed that predict contacts in protein structures from a multiple sequence alignment of homologous sequences. We explore the potential of these predictions for fold recognition by developing an algorithm that makes no use of amino acid identity, and so should be agnostic to the existence of a ‘twilight zone’. We show that whilst this is not the case, our method is complementary to state-of-the-art approaches.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:595946 |
| Date | January 2013 |
| Creators | Hill, Jamie Richard |
| Contributors | Deane, Charlotte M. |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://ora.ox.ac.uk/objects/uuid:353a9832-b2a4-41fb-a9f2-f3cae1a30039 |
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