Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.655081
Title: Computational studies of protein helix kinks
Author: Wilman, Henry R.
ISNI:       0000 0004 5361 9210
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2014
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Abstract:
Kinks are functionally important structural features found in the alpha-helices of many proteins, particularly membrane proteins. Structurally, they are points at which a helix abruptly changes direction. Previous kink definition and identification methods often disagree with one another. Here I describe three novel methods to characterise kinks, which improve on existing approaches. First, Kink Finder, a computational method that consistently locates kinks and estimates the error in the kink angle. Second the B statistic, a statistically robust method for identifying kinks. Third, Alpha Helices Assessed by Humans, a crowdsourcing approach that provided a gold-standard data set on which to train and compare existing kink identification methods. In this thesis, I show that kinks are a feature of long -helices in both soluble and membrane proteins, rather than just transmembrane -helices. Characteristics of kinks in the two types of proteins are similar, with Proline being the dominant feature in both types of protein. In soluble proteins, kinked helices also have a clear structural preference in that they typically point into the solvent. I also explored the conservation of kinks in homologous proteins. I found examples of conserved and non-conserved kinks in both the helix pairs and the helix families. Helix pairs with non-conserved kinks generally have less similar sequences than helix pairs with conserved kinks. I identified helix families that show highly conserved kinks, and families that contain non-conserved kinks, suggesting that some kinks may be flexible points in protein structures.
Supervisor: Deane, Charlotte M.; Shi, Jiye Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.655081  DOI: Not available
Keywords: Bioinformatics (biochemistry) ; Life Sciences ; Bioinformatics (life sciences) ; Computational chemistry ; Membrane proteins ; Protein chemistry ; Mathematical genetics and bioinformatics (statistics) ; Physical Sciences ; Polymers Amino acid and peptide chemistry ; Bioinformatics (technology) ; Technology and Applied Sciences ; Protein ; Helix ; Kink ; Secondary structure ; Structural biology ; protein structure prediction ; crowdsourcing
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