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Protein fold evolution on completed genomes : distinguishing between young and old folds

We review fold usage on completed genomes in order to explore protein structure evolution and assess the evolutionary relevance of current structural classification systems (SCOP and CATH). We assign folds on a set of 150 completed genomes using fold recognition methods (PSI-BLAST, SUPERFAMILY and Gene3D). The patterns of presence or absence of folds on genomes gives us insights into the relationships between folds and how we have arrived at the set of folds we see today. In particular, we develop a technique to estimate the relative ages of a protein fold based on genomic occurrence patterns in a phylogeny. We find that SCOP's `alpha/beta' class has relatively fewer distinct folds on large genomes, and that folds of this class tend to be older; folds of SCOP's `small protein' class follow opposite trends. Usage patterns show that folds with many copies on a genome are generally old, but that old folds do not necessarily have many copies. In addition, longer domains tend to be older and hydrophobic amino acids have high propensities for older folds whereas, polar - but non-charged - amino acids are associated with younger folds. Generally domains with stabilising features tend to be older. We also show that the reliability of fold recognition methods may be assessed using occurrence patterns. We develop a method, that detects false positives by identifying isolated occurrences in a phylogeny of species, and is able to improve genome wide fold recognition assignment sets. We use a structural fragment library to investigate evolutionary links between protein folds. We show that 'older' folds have relatively more such links than 'younger' folds. This correlation becomes stronger for longer fragment lengths suggesting that such links may reflect evolutionary relatedness.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:441063
Date January 2007
CreatorsAbeln, Sanne
ContributorsDeane, Charlotte M.
PublisherUniversity of Oxford
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://ora.ox.ac.uk/objects/uuid:b520fd65-e829-4ae0-bed6-47d642909889

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