H. William Detrich, Kostia Bergman, Veronica S. Godoy-Carter, Mary Jo Ondrechen
Date of Award
Doctor of Philosophy
Department or Academic Unit
College of Arts and Sciences. Department of Biology.
Biology, Bioinformatics, Comparative functional genomics, Comparative protein modeling
Molecular association, Microbial genetics
Biochemistry, Biophysics, and Structural Biology
The three-dimensional structure of a protein provides important information for understanding and answering many biological questions in molecular detail. The rapidly growing number of sequenced genes and related genomic information is intensively accumulating in the biological databases. It is significantly important to combine biological data and developing bioinformatics tools while information of protein sequences, structures and DNA sequences are exponentially growing. On the other hand, especially the number of known protein sequences is much larger than the number of experimentally solved protein structures. However the experimental methods cannot always be applied or protein structures cannot be available for all protein sequences. Comparative protein modeling technique is closing a gap for the protein sequences with unknown structures by constructing a three-dimensional model of a given protein sequence based on sequence similarity to one or more known structures. I present here several different applications of comparative protein modeling by developing servers for mapping nsSNPs on to comparative protein models, studying comparative functional genomics of HMGN3a and SMARCAL1 along with multiple sequence analysis, developing comparative models for other techniques in order to find active sites, and understanding the possible functional properties of proteins while substitutions occur in a given protein. Part of the presented research focused on nonsynonymous SNPs, understanding the functional consequences of nonsynonymous changes and predicting potential causes and the molecular basis of diseases involves integration of information from multiple heterogeneous sources including sequence, structure data and pathway relations between proteins. In order to visualize them on protein structures and perform the analysis on nsSNP, a web server, Structure SNP (StSNP) was developed. It provides the ability to analyze and compare human nsSNP(s) in protein structures, protein complexes and protein-protein interfaces, where nsSNP and structure data on protein complexes are available in PDB. In the second part of the research, comparative functional genomics analysis of HMGN3a and SMARCAL1 was studied along with combining information with comparative modeling and multiple protein sequence analysis across mammals. Our results showed that there was a high degree of structural conservation of HMGN3a and SMARCAL1 in the mammalian species studied. In the third part of the research several comparative models built from different species in order to find active site residues by the THEMATICS method. In the last part of the research multiple sequence alignment studies of APEX1 and dna polymerase beta and comparative models of gamma-tubulins were studied and presented.
Uzun, Alper, "Bioinformatics applications through visualization of variations on protein structures, comparative functional genomics, and comparative modeling for protein structure studies" (2009). Biology Dissertations. Paper 1. http://hdl.handle.net/2047/d10019480
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