Protein-protein interactions as a basis for drug target identification

Interactions between proteins are some of the most important and interesting events taking place in almost every cell. The elucidation of their nature is one of the challenges to be undertaken in order to answer many of the questions that have resulted from the recent sequencing of the human genome. There is a need for new techniques to be able to characterise functionally all the proteins encoded by a genome. Clues to the function of a protein can be obtained by seeing whether it interacts with another protein of known function (the principle of "guilt by association"). Proteins that interact with one another usually participate in the same or related cellular functions. Since almost all cellular processes are regulated by multiprotein complexes, the absence of interactions or non-physiological interactions are often the cause of disease in humans. Identification of these proteins is of great interest since they are often subsequently used as target proteins in screening for lead compounds that have the potential to regulate these interactions. The identification of protein interactions was initially detected by biochemical methods but these are not suitable for large-scale screenings; more recently, yeast two-hybrid systems have been employed as powerful genetic tools to find proteins in their native comformation that interact specifically with a protein of interest in highthroughput screening (1, 2). One important advantage of the yeast two-hybrid system compared with other techniques is the applicability of this in vivo method to a high-throughput scale. As a consequence, comprehensive proteininteraction maps containing all known interactions between the proteins in a given organism have been constructed (3, 4, 5). The DUALhybrid screen is a customised and optimised yeast two-hybrid screen developed by Dualsystems Biotech AG (Zürich, Switzerland); with its quality controlled screening service, the company aims to bridge effectively the gap between genetic information and drug discovery for the treatment of human disease.