Cardiovascular drug target identification via disordered protein analysis focus

DESCRIPTION (provided by applicant): A certain type of protein-protein interaction can be blocked using small molecules. This type of interaction involves a disorder-to-order transition of a molecular recognition element on one protein binding to a receptor site on another. Application of our proprietary bioinformatics software called PONDR(r) to a substantial set of cardiovascular disease (CVD)-associated proteins revealed that greater than 60% of these proteins are likely to contain disordered regions of substantial size and these regions contain a large number of molecular recognition elements. To exploit these preliminary findings, we will construct an annotated database of CVD proteins, "CardioVascular DisProt (CVD DisProt)," correlating disorder/order to proteins' functions. This new database will contain disorder/order predictions and existing structural knowledge correlated with collected functions of CVD-associated proteins and augmented with information of protein interaction networks. Next, our preliminary bioinformatics tools will be enhanced for the purpose of identifying druggable protein-protein interactions. The products developed in this project will form a new, powerful research tool, which will be used by pharmaceutical and biotechnology companies to improve prioritization of novel drug targets. CVD researchers could use relationships between function and order/disorder propensity to discover new proteins involved in signaling pathways of interest. Structural genomics centers would find CVD DisProt indispensable as a source of biologically relevant, ordered domains for structure determination. Finally, and most importantly, using the enhanced PONDR(r) tools, the CVD DisProt will be datamined to yield a ranked list of druggable protein-protein interactions. This will provide the starting point for a novel pathway for drug discovery.