Saturday, November 23, 2024
11/23/2024
ABSTRACT With the recent revolution in artificial intelligence for molecular design and protein structure prediction, we were motivated to apply these new tools to address bottlenecks in our research focusing on retroviral entry, integration, and drug design. Viral entry and receptor usage has become a major focus with the emergence of new viruses with expanded host and tissue specificities. Our research focuses on the ability of retroviral Envelopes to select and utilize novel host cell receptors. In this proposal, we are utilizing new approaches to identify and study two novel retroviral Env proteins and their host cell receptors. These include the binding of the A5/A9a Env protein to the host membrane protein SLC35F2 and the identification of the cognate receptor(s) for the L1 Env. Applying AlphaFold2, Phyre2 and Evolutionary Covariance structure prediction programs, we have a first generation model for SLC35F2, which serves as the foundation for a broad number of questions relating to the function of this orphan receptor. The second area of focus builds on the gammaretroviral Integrase (IN) protein binding to the host BET proteins. Through our structural studies of both the Murine Leukemia Leukemia (MLV) IN protein and the host NSD3 protein binding to the ET domain of the Brd3 BET protein, we are now able to apply our knowledge of the common binding pocket to advance approaches for studies of alternative binding substrates and small molecule inhibitors. The ET domain of the BET family of proteins serves as a node for multi-protein assemblies. Understanding the affinity of different proteins and small molecules to this ET binding pocket can have profound effects of gammaretroviral pathogenesis as well as gene and oncogene regulation. Using computer-aided drug discovery approaches, we have identified first-in-class lead compounds targeting the ET domain. These studies build on our cohesive collaborative research team with expertise in virology, NMR structural studies, and bioinformatics.
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