Computational Design of Protein-Protein Interactions

Univ Of North Carolina Chapel Hill, Chapel Hill NC

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Abstract

? DESCRIPTION (provided by applicant): Protein-protein interactions are essential to almost all biological processes. Engineered proteins with novel binding properties are used as therapeutics and are important tools for cellular and biomolecular research. The objective of the research described here is to develop and test computational methods for manipulating the affinities and specificities of protein-protein interactions. This is an ongoing project and during the previous funding period we made exciting progress in several areas, including the high-accuracy design of new protein complexes. Important to this success were the development of improved energy functions and approaches for sampling regions of conformational space that are inherently designable. Here, we propose to continue developing innovative strategies for interface design while using these methods to engineer proteins for controlling and monitoring GTPase signaling in living cells. Spatiotemporal regulation of GTPase activity is critical for a wide variety of cellular events, and engineered proteins that can be used to determine when and where GTPases are activated will allow cell biologists to better understand feedback processes in these signaling networks. Each of our specific aims focuses on a different aspect of interface design. In Aim 1 we will use a new strategy for the de novo design of proteins to stabilize binding epitopes by embedding them in folded proteins and create competitive inhibitors against the G-protein G?q. Binding affinity measurements, site-directed mutagenesis and high-resolution structure determination will be used to evaluate the computational predictions. In Aim 2 we will simultaneously model alternative binding conformations when designing sequences that favor one binding partner over another. We will use this new approach to redesign GTPase biosensors so that they are less likely to perturb the system that they are monitoring. In aim 3 we will use computationally directed libraries along with yeast display to engineer dye-based biosensors for live cell imaging. By pursuing this project we will expand the capabilities of computational protein design and test our understanding of the primary determinants of affinity and specificity at protein-protein interfaces.