| In the past several decades, exciting research has elucidated that the structural dynamics of proteins have a profound impact on their activities. Molecular dynamics (MD) simulations have become a powerful means of exploring the ensembles of structures accessible to proteins, in order to compute thermodynamic properties that allow us to understand the forces that drive the binding of a drug to its receptor, or even the formation of macromolecular assemblages. The research presented in this dissertation utilizes MD simulations, among other computational techniques, introduced in Chapter 1, to further our understanding of the activation mechanism of histone deacetylase 3 (HDAC3), a promising target for epigenetic cancer therapy. The enzymatic activity of HDAC3 depends on its binding to other proteins and a small moelcule, inositol tetraphosphate (IP4). In Chapter 2, we show how the binding of HDAC3 to a deacetylase activating domain and to IP4 restrain the dynamics of HDAC3, suggesting a single active HDAC3 conformation. In Chapter 3, we show that the dynamics of HDAC3 can be similarly stabilized by mutating a single residue near the IP4-binding site, shedding light on the long-range allosteric networks that must be conserved for the deacetylase activity of HDAC3. In Chapter 4, we show that the restrained conformational ensembles of HDAC3 have predictive power in identifying known HDAC inhibitors among decoy drug-like molecules, and perform a structure-based virtual screen for novel active site and allosteric inhibitors. One of the challenges in using MD simulations to address these types of questions for systems is the extent to which an MD trajectory can indeed represent the conformational ensemble of the system. In Chapter 5, we present a method that aims to enhance the sampling of relevant conformations, particularly for a problematic system with kinetically "trapped" conformations. |
