Hatice Gulcin Ozer

My Story:

Thesis title:
Residue Associations In Protein Family Alignments

Abstract:
The increasing amount of data on biomolecule sequences and their multiple alignments for families, has promoted an interest in discovering structural and functional characteristics of proteins from sequence alone. In many proteins interactions between residues appear to be key players in structure and function. Consensus, or weight matrix, or hidden Markov models cannot detect interpositional correlations and alternating motifs within a family alignment. We propose and analyze a method for detecting interpositional correlations and examine the applicability of this method to structural prediction.
We presented the Multiple Alignment Variation Linker (MAVL) and StickWRLD to analyze biomolecule sequence alignments and visualize positive and negative interpositional residue associations. In the MAVL analysis system, the expected number of sequences that should share identities and residuals are calculated based on the observed population of sequences actually sharing the residues. Correlating pairs of residues are visualized in StickWRLD diagram. This analysis system allows us to extract information from the alignments which is not accessible to traditional column-based methods. In addition, a StickWRLD diagram enables the user to visualize the family alignment and positional dependencies in 3D.
We discuss methodologies to identify residue associations in protein family alignments. We discussed the use of the residuals and the phi coefficient to determine the strength of a residue association, and Fisher Exact probability test to evaluate the statistical significances. We computed identitywise residue associations for 961 Pfam family alignments and examined physical proximity and physiochemical properties of associated residues in the alignments and their presence on secondary structural elements. We observed that the proximity of residues increases as the strength of association and its statistical significance increase. Specifically, associations between aromatic residues and hydrophilic residues are present in closer proximity. The amino acid contact predictivity of the residual parameter is the highest compared to the phi coefficient and the statistical significance. Compared to the expected distributions, we observed larger proportions of the pairs such that both residues are in a helix or one residue is in a structural element while the other is in a flexible region, or both residues are in a flexible region.