Classification of Protein Domain Movements using Dynamic Contact Graphs

Taylor, Daniel (2014) Classification of Protein Domain Movements using Dynamic Contact Graphs. Doctoral thesis, University of East Anglia.

Preview

PDF Download (19MB) | Preview

Abstract

Protein domain movements are of critical importance for understanding macromolecular
function, but little is understood about how they are controlled, their energetics, and how
to characterize them into meaningful descriptions for the purpose of understanding their
relation to function. Here we have developed new methods for this purpose based on changes
in residue contacts between domains. The main tool used is the “Dynamic Contact Graph”
which in one static graph depicts changes in contacts between residues from the domains.
The power of this method is twofold: first the graphs allow one to use the algorithms of graph
theory in the analysis of domain movements, and second they provide a visual metaphor
for the movements they depict. Using this method it was possible to classify 1822 domain
movements from the “Non-Redundant Database of Protein Domain Movements” into sixteen
different classes by decomposing the graphs for each individual protein into four elemental
graphs which represent the four types of elemental contact change. For each individual
domain movement the output of this process provides the numbers of occurrences of each
type of elemental contact change. These were used as input for logistic regression to create a
predictor of hinge and shear using assignments for these two mechanisms at the "Database
of Macromolecular Movements". This predictor was applied to the 1822 domain movements
to give a tenfold increase in the number of examples classified as hinge and shear. Using this
dataset it was shown that contrary to common interpretation there is no difference between
hinge and shear domain movements. The new data is presented online with new websites
which give visual depictions of the protein domain movements.

Item Type:	Thesis (Doctoral)
Faculty \ School:	Faculty of Science > School of Computing Sciences
Depositing User:	Users 2259 not found.
Date Deposited:	01 Jul 2015 08:47
Last Modified:	01 Jul 2015 08:47
URI:	https://ueaeprints.uea.ac.uk/id/eprint/53442
DOI:

Downloads

Actions (login required)

View Item