Abstract:
Proteins are crucial to the development of multicellular organisms. These microscopic machines serve a wide range of jobs—from transporting small molecules to catalyzing biochemical reactions. In recent years, advances in computational molecular modeling and knowledge of protein structure and function have significantly progressed to the point where we can now create artificial proteins. However, giving functionality to a protein is the next demanding task at hand. The Smith Lab aims to optimize the function of a de novo β-barrel protein termed mini-Fluorescence Activating Protein (mFAP), which stabilizes GFP-mimetic compound 3,5-difluoro-4-hydroxybenzylidene-imidazolinone (DFHBI) in the hydrophobic binding cavity. Instead of arbitrarily picking point mutations, we intend to increase the brightness of the mFAP-DFHBI complex by using the Rosetta, a molecular modeling software, which has two useful features: 1) the ability to easily create point mutations and 2) output change in energy estimates of how stabilizing or destabilizing a mutation can be for increasing brightness. From Rosetta’s predictions, we then select the best stabilizing candidates for molecular dynamic (MD) validation. Our MD results suggest that some of the stabilizing Rosetta predictions can increase the brightness of DFHBI, however in other cases, it does not. This research involved in optimizing protein-ligand complexes can be applied in mechanistic aspects of enzyme catalysis or more broadly, clinical fieldwork.
Video:
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Thursday, July 29th 1:15-2:30pm EDT