Pleckstrin homology domains.

Abstract

Pleckstrin homology (PH) domains are small protein modules of around 120 amino acids that are found in a large number of proteins involved in intracellular signaling and cytoskeletal organization, often occurring alongside SH2, SH3, PTB and other domains discussed in this volume. PH domains were first noted by Mayer et al. (1993) and Haslam et al. (1993) as sequences found in a number of intracellular signaling molecules that show limited homology to a region repeated in the protein pleckstrin (Tyers et al. 1988). As a result, this 47-kDa protein, which is the major substrate of protein kinase C (PKC) in platelets, has lent its name to a domain now identified in more than 100 different proteins involved in different signaling and cytoskeletal organization processes. Soon after the identification of the PH domain, structural studies showed that it does indeed form an independent module with a characteristic β-sandwich structure. The functions of PH domains are now becoming more clear, and the current view is that they are involved in recruitment of their host proteins to cell membranes. In some cases this recruitment is achieved through direct interaction of the PH domain with specific membrane components, and can be directly signal-dependent — with the PH domain binding to a lipid second messenger. In this chapter, we will discuss the structure of PH domains, and the characteristics that make them ideally suited for binding to the membrane surface. We will also review the current state of knowledge regarding PH domain function and ligand-binding properties, and will consider how they may participate in defining the specificity of intermolecular interactions and compartmentalization required for the function of their host proteins in signaling processes.KeywordsInositol PhosphateGuanine Nucleotide Exchange FactorPleckstrin HomologyMembrane AssociationPleckstrin Homology DomainThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.