Computational Mapping of Proteins for Binding of Ligands

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DESCRIPTION (provided by applicant): This proposal is the competitive revision (Notice NOT-OD-09-58, NIH Announces the Availability of Recovery Act Funds for Competitive Revision Applications) of the grant "Computational Mapping of Proteins for the Binding of Ligands". Mapping methods place molecular probes - small molecules or functional groups - on the surface of proteins in order to identify the most favorable binding positions. Since regions of the protein surface that are major contributors to the binding free energy in drug-protein interactions also bind a variety of small organic molecules, mapping can identify such "hot spots" and the number of probe molecules bound is a good predictor of druggability. The parent proposal focused on "traditional" drug targets that naturally bind small molecular ligands. The general goal of this revision is to extend the analysis to the identification and characterization of druggable sites in protein-protein interfaces. Such analysis facilitates the discovery of small molecules that can inhibit or modulate the association of two proteins, an important emerging problem in pharmaceutical research. Application of mapping to a number of protein-protein interaction (PPI) targets has shown that the method always identifies at least some fraction of the site which can bind small molecular inhibitors within the protein-protein interface region, even when starting from the structure of a ligand-free protein. In Aim 1 we will further study the generality of this observation by mapping a variety of PPI targets on which structural and biochemical information is available. We will also study the interactions between fragments and their protein environments in the binding site by using target-specific probe libraries based on the known ligands of each target. Since binding of small molecules frequently requires conformational changes to form appropriate pockets in a relatively flat protein-protein interface, in Aim 2 we develop a method to account for side chain flexibility prior to mapping. The algorithm combines statistical analysis and energy minimization to identify "moveable" side chains and their potential conformational states in the vicinity of the "hot spot" identified by the initial mapping. Protein structures are generated by combining the potential conformations of moveable side chains. The re-mapping of such adjusted structures generally agrees well with results obtained for the ligand-bound proteins, and hence substantially improves the predictive power of the method. Aim 3 is the theoretical and experimental characterization of hot spots that enable the binding of small molecular inhibitors in the binding interface of IL-2 with IL-2R1, an exemplary PPI target. The binding energies that different portions of the known inhibitors derive from their interactions with the protein have not been systematically elucidated. We will measure experimental binding energies and binding orientations for different molecular fragments derived from these known IL-2 inhibitors, using quantitative biochemical and biophysical assays as well as X-ray crystallography, and will compare the results with those obtained computationally using these same fragments as probes. The results will provide new information on the physicochemical and structural features that render a difficult PPI site druggable, which we will use to further refine our computational method. PUBLIC HEALTH RELEVANCE: Mapping methods place molecular probes - small molecules or functional groups - on the surface of proteins in order to identify the most favorable binding positions, and provide information on the druggability of such site. We focus on the identification and characterization of druggable sites capable of binding small molecular inhibitors of protein-protein interactions, an important emerging problem in pharmaceutical research.