Scott P. Morton
ABSTRACT
Research in the field of HIV transmission has yet to provide a vaccine for this imponderable virus. Though progress has been made to extend the life of those chronically infected, a solution to the transmission of the disease remains elusive. Previous studies involving electrostatic surface charge analysis revealed the sensitivity of gp120 envelope (Env) protein function to changes in pH across levels consistent with those found in the human body. A prototype computational approach was developed and found to agree with these results. A refined process was developed capable of classifying Env sequences/structures through machine learning techniques. We expound this analytical procedure to encompass residue-level analysis and include minimization steps to ensure the integrity of the protein models. Additionally, the process has been enhanced with advanced data compression techniques to allow for more in-depth analysis of the systems. In this research we explore a new technique termed electrostatic variance masking (EVM), that reveals what we hypothesize to be the mechanistic residues responsible for the pH sensitivity of Env binding site. The data implies that a conserved set of core residues may be responsible for modulation of the binding process in varying environmental conditions mainly involving pH.
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Index Terms
- Sub-Class Differences of PH-Dependent HIV GP120-CD4 Interactions
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