Decades of research have yet to provide a vaccine for the human immunodeficiency virus which causes acquired immune deficiency syndrome. The virus sequence varies at high rates once infection occurs, but changes in the RNA sequence that defines the virus are further convoluted by the limited number of variations that can infecting another host during heterosexual intercourse. Current theoretical research has turned attention to genital mucosa pH levels over systemic pH levels in the quest to determine the transmission bottleneck observed. Previous research in this field developed a computational approach for determining pH sensitivity that indicated higher potential for transmission at mucosa pH levels present during intercourse. The process was extended to incorporate multiple program / multiple data operations, advanced compression for accumulated data and a principal component analysis (PCA)-based machine learning technique for classification of gp120 proteins against a known transmitted variant; This method is called Biomolecular Electro-Static Indexing (BESI). The process was further extended to the residue level by a method termed Electrostatic Variance Masking (EVM) and used in conjunction with BESI to determine structural differences present among various subspecies across HIV Clade. Results indicate that variable loop composition outside of the core selected by EVM may be responsible for binding affinity observed in many other studies and that pH modulation of residues selected by EVM may influence specific regions of the viral envelope protein involved in protein-protein interactions. Further research has shown that pH affects binding free energy, a measure of contribution solvation has for interactions between two molecules. These data indicate that a functional range of pH exists and is different for gp120/CD4 interactions compared to gp120/broadly neutralizing antibody interactions. The methods presented in this dissertation have been applied extensively to HIV gp120 proteins individually and in protein-protein interaction simulations. Protein interaction simulations for gp120 with human CD4 protein (found on the surface of T lymphocytes, monocytes, dendritic cells and brain microglia), and gp120 with broadly neutralizing antibodies provide unique insight not easily or economically achievable with traditional laboratory methods. The pipeline and methods are easily adapted to other protein structures, such as SARS-CoV-2 spike protein with human angiotensin-converting enzyme 2, and should provide valuable and unique insights into interactions where environmental factors, like pH, may modulate how two proteins interact.
|Advisor:||Phillips, Joshua L.|
|Commitee:||Kong, Jing, Leander, Rachel, Wright, Stephen|
|School:||Middle Tennessee State University|
|Department:||College of Basic & Applied Sciences|
|School Location:||United States -- Tennessee|
|Source:||DAI-B 82/3(E), Dissertation Abstracts International|
|Keywords:||Electrostatics, Gp120, HIV, pH|
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