Calculating the structure-based phylogenetic relationship of distantly related homologous proteins utilizing maximum likelihood structural alignment combinatorics and a novel structural molecular clock hypothesis

Abstract

Dendrograms establish the evolutionary relationships and homology of species, proteins, or genes. Homology modeling, ligand binding, and pharmaceutical testing all depend upon the homology ascertained by dendrograms. Regardless of the specific algorithm, all dendrograms that ascertain protein evolutionary homology are generated utilizing polypeptide sequences. However, because protein structures superiorly conserve homology and contain more biochemical information than their associated protein sequences, I hypothesize that utilizing the structure of a protein instead of its sequence will generate a superior dendrogram. Generating a dendrogram utilizing protein structure requires a unique methodology and novel bioinformatic programs to implement this methodology. Contained within this dissertation is an original methodology that permits the aforementioned structure-based iv dendrogram generation hypothesis. Additionally, I have scripted three novel bioinformatics programs required by this proposed methodology: a protein structure alignment program that proficiently superimposes distant homologs, an accurate structure-dependent sequence alignment program, and a dendrogram generation program that employs a novel structural molecular clock hypothesis. The results from this methodology support the proposed hypothesis by demonstrating that generating dendrograms utilizing protein structures is superior to those generated utilizing exclusively protein sequences.