Evaluation and application of computational strategies for exploring the dynamics and small-molecule binding properties of proteins

Protein functions are determined by their intrinsic dynamics. In order to affect the functions of certain proteins many drugs impact the dynamics of their target protein, either through their interactions directly or by altering interactions with other binding partners. Allosteric drugs, those that target sites on proteins distal from their active sites, provide a way to finely tune the dynamics of proteins of interest without directly competing with endogenous ligands while also generally being less promiscuous due to the lower evolutionary conservation of allosteric sites compared to orthosteric sites. A crucial step for the development of allosteric drugs is the understanding of the intrinsic dynamics of proteins of interest. In this dissertation I show the application of protein dynamics analysis using Gaussian Network Models (GNMs) at the domain and family level in order to characterize the dynamics of PDZ domain and Class A G Protein Coupled Receptors (GPCRs). I also present my work evaluating virtual screening strategies as part of the 2016 Drug Design Data Resource (D3R) competition, a community-wide virtual screening competition funded by the NIH. And lastly, I apply dynamics analysis and virtual screening methods towards the goal of developing novel Poly [ADP-ribose] polymerase 1 (PARP1) inhibitors for the treatment of traumatic brain injury.