PI-Fish: A Novel approach for discovering druggable sites in cancer proteins

DESCRIPTION (provided by applicant): Project Summary. In the predominant sequence-to-function paradigm, 3-D structure is an obligatory . prerequisite for protein function. This paradigm dominates thinking about drug discovery. Even though over 100 counter examples not following this paradigm are described in literature, the functions associated with these non-folded (disordered) protein has been mostly ignored. To the contrary, the analysis of oncogenic proteins reveals that they possess more functional intrinsic disorder than other protein types. In many cases, the interaction of an oncoprotein with one or more binding partners involves disorder-to-order transitions. Recently, small molecules have been developed that block protein-protein interactions involving at least one oncoprotein. The main goal of the project is to develop a set of computational and experimental methods, called Protein Interaction (Pl)-fish, that can be used to find druggable protein-protein interaction sites involving disorder-to-order transitions in cancer-related proteins. This will be done via the development of a ranked list of potential protein-protein interactions that show promise for drug targeting. The list will be populated using our proprietary software, predictor of alpha-helical molecular recognition elements (alpha- MoRE predictor). The usefulness of the resulting predictions will be validated by showing that the indicated alpha-MoRE peptides can be used to fish out their binding partners from cell extracts. Pi-fish will help in the identification of duggable interactions and thereby provide the starting point for the development of drug leads. Relevance. Finding molecules that modulate the signaling activities of proteins involved in the development of cancer represents an extremely attractive approach to drug discovery. This approach, however, has been mostly disappointing in practice. The application of Pi-fish tool is suggested to be likely to dramatically accelerate the early stages of drug discovery because it is based on new structural principles. The long- range goal will be to use these results to develop an entirely new class of anti-cancer drugs.