Barber, MatthewPaterson, Nicole2021-09-132021-09-132021-09-13https://hdl.handle.net/1794/26672Pathogens and parasites have evolved effective strategies to gain access to host resources. The immune system fends off these attacks, often through detection of pathogen associated molecules and clearance of infection. This results in interactions between host and pathogen that often take place at molecular interfaces of immune receptors that act as a first line of defense to infection. Such receptors must identify pathogen-specific molecules and mount an appropriate response. Due to the frequency of such high stakes interactions between immune receptors and pathogen-derived molecules, the immune system is under constant evolutionary pressure to innovate new modes of defense and detection, while the pathogen is under pressure to evade these efforts and mount offensive attacks. This dynamic, called evolutionary conflict, is the underlying evolutionary principle inspiring this work. Because proteins evolve functions through DNA modifications, we study the effects of nucleotide variation across related species and test how variation affects the dynamics of protein interactions. We show that phylogenetic relationship is not a good indicator of functional similarity in the systems we tested. In the first study in Chapter II, we found that presence of certain amino acids in ligand-binding hotspots are more likely to have an effect on whether a Staphylococcus aureus inhibitor binds to immune receptor than overall sequence homology. In the second study that comprises Chapter III, we found a similar lack of correlation between predicted functional outcomes and familial relationship. Similar to the study in Chapter II, we found that certain sites could have an outsized effect on function that could be translated across multiple species. Interestingly, site-level similarities at “hotspot” regions were a better indicator of function than phylogenetic relationships.en-USAll Rights Reserved.Adaptive EvolutionCD1aFPR1FPR2Immune SystemPositive SelectionElectronic Thesis or Dissertation