Protein-protein interactions determine the outcome of all cellular processes including signal transduction, cell division, DNA replication, transcription and translation, biosynthesis, and degradation. Hence, modulating protein-protein interactions is of great interest for both basic science and applied research such as drug design. Directed evolution and combinatorial screening techniques are powerful and well-established means of engineering protein complexes with enhanced affinity and binding specificity. Although very successful in obtaining the end product, these techniques do not address some basic questions such as what makes a particular protein a high-affinity binder or how to obtain a protein with slightly different binding characteristics. Computational approaches to modulating protein-protein interactions are directed toward answering these fundamental questions. These approaches, in principle, provide a fast and efficient way to supply proteins with desired binding properties. However, computational techniques require high-resolution structures for the protein-protein complexes, which are not always available. In addition, they rely on our still incomplete knowledge of the physical basis for protein binding affinity and specificity. Due to these limitations, relatively few successful examples of computationally designed protein-protein interactions have been reported. However, even when not completely successful, investigations of this type greatly advance our understanding of the molecular forces that govern protein binding. With the exponentially growing number of new structures of protein-protein complexes and a constant progress in method development, computational approaches are evolving into a generally accepted strategy for modulating protein-protein interactions. This chapter reviews the methods for design of protein-protein interactions, summarizes keystone studies in this area, and points out future directions of research.
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© 2009 by Taylor and Francis Group, LLC.