Structural Analysis of TF and Interacting Molecules

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The ability to precisely identify and characterize the molecular sites of interaction, both for the coagulation protease pathway and for the signaling pathways related to thrombogenesis, will open the door for computational and experimental screening of chemical agents that may beneficially modulate these processes. The identification of such agents may generate new classes of interventional molecules to study these mechanisms in greater detail and may lead to new diagnostic and therapeutic approaches to the detection and treatment of the thrombotic and related diseases. The goal of this project is to produce a physical picture of the interactions of Tissue Factor (TF) with its functionally relevant partners, and to utilize this information to help select targets and design chemical agents that can modulate TF function in vitro and in vivo. To accomplish this we will determine and analyze the structural aspects of the intracellular and extracellular molecular interactions of Tissue Factor by utilizing and combining computational modeling, NMR and other biophysical methods. We will use these structures to define binding sites and interaction "hot spots", computationally screen small molecule libraries, and design specific ligands to modulate particular interactions. Specifically we will utilize computational docking, and molecular mechanics to develop improved models of the temary complexes of tissue factor/factor Vlla with factors IXa and Xa; model interactions of peptide inhibitors with the ternary complex containing Xa; develop models for the extracellular interactions of the initiation complex with the protease activated receptors PAR-1 and PAR-2; and develop models of the interaction of TF with relevant integrin structures. Utilizing NMR, and other biophysical techniques in conjunction with computational modeling, we will characterize the intracellular interactions of the cytoplasmic TF C-terminal domain (TFCD) in both its phosphorylated and unphosphorylated states with signaling partners. From these structural analyses we will define interaction targets and screen small molecule databases for ligands that can modulate these interactions. To enable these studies we will extend and enhance our computational docking codes to deal with the complexity of these multi-component, flexible molecular systems.