An Analysis of Ancestral Sequence Resurrection in the Context of Guanylate Kinase Evolution
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Ancestral sequence resurrection (ASR) is an important tool for studying evolution on a molecular scale. The process takes a broad range of extant samples and, using sequence alignment and evolutionary prediction algorithms, determines the most likely sequence to have evolved into modern-day proteins. While ever-improving technologies allow for increasingly reliable predictions, it is impossible to prove whether a reconstruction is in fact the true ancestor. This project will analyze the fidelity of the ASR process in the context of the divergence of enzymatically inactive guanylate kinase-like binding domains and enzymatically active guanylate kinases from a common ancestor. A maximum likelihood ancestor has already been predicted, so by comparing relative enzymatic activity of this ancestor, a variety of mutants, Bayesian predictions, and extant enzymes, we will be able to assess the validity of ASR for this billion-year-old evolutionary event.