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STRUCTURAL DETERMINANTS OF REPLACEMENT RATE HETEROGENEITY

<p> Protein sequences display replacement rate heterogeneity across sites. In an earlier
work, half of the causal site-wise variation in replacement rates was explained
by a simple linear regression model consisting of terms for the solvent exposure of
each residue, distance from the active site, and glycines in unusual main-chain conformations.
Replacement rates vary not only across sites, they may also vary over
time. In this study, we apply the linear regression model to phylogenies divided
into subtrees to see if lineage-specific rate shifts have a structural basis that can be
detected by the model. This approach is applied to two different data sets. The first
set consists of phylogenies containing two representative structures, divided into
subtrees such that one structure is present in each subtree. These structures have
little or no obvious functional divergence between them. The model is tested with
permutations of subtrees and structures from each subtree. While there is a slight
effect of the specific structure on the fit of the model, the specific subtree has a
greater effect. The second data set involves homologous structure pairs where the
quaternary structure has changed at some point in the phylogeny. These pairs are
examined to see how the change in constraint on the new interface sites affect the
replacement rate, and its relationship with other structural factors. We find that the
unique interfaces are as conserved as the shared ones, and they exhibit a different
relationship between replacement rates and indicators of constraint than the shared
interfaces or other protein sites. We also find that the unique interfaces display
characteristic amino acid preferences that may identify interfaces which are still in
the process of stabilizing. </p> / Thesis / Master of Science (MSc)

Identiferoai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/21654
Date07 1900
CreatorsRaftis, Francis
ContributorsGolding, Brian, Biology
Source SetsMcMaster University
LanguageEnglish
Detected LanguageEnglish

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