Computational chemistry plays a vital role in understanding chemical and physical processes and has been useful in advancing the understanding of reactions in biology. Improper signaling of the nuclear factor-κB (NF-κB) pathway plays a critical role in many inflammatory disease states, including cancer, stroke, and viral infections. Aberrant regulation of this pathway happens upon the signal-induced degradation of the inhibitor of κB (IκB) proteins. The activation of IκB kinase (IKK) subunit β (IKKβ) or NF-κB Inducing Kinase (NIK), initiates this cascade of events. Understanding the structure-property relationships associated with IKKβ and NIK is essential for the development of prevention strategies. Although the signaling pathways are known, how the molecular mechanisms respond to changes in the intracellular microenvironment (i.e., pH, ionic strength, temperature) remains elusive. In this dissertation, computer simulation and modeling techniques were used investigate two protein kinases complexed with either small molecule activators or inhibitors in the active, inactive, and mutant states to correlate structure-property and structure-function relationships as a function of intracellular ionic strength. Additionally, radical-induced protein fragmentation pathways, as a result of reactions with reactive oxygen species, were investigated to yield insight into the thermodynamic preference of the fragmentation mechanisms. Analyses of the relationship between structure-activity and conformational-activity indicate that the protein-protein interactions and the binding of small molecules are sensitive to changes in the ionic strength and that there are several factors that influence the selectivity of peptide backbone cleavage. As there are many computational approaches for predicting physical and chemical properties, several methods were considered for the predictions of protein-protein dissociation, protein backbone fragmentation, and partition coefficients of drug-like molecules.
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