A quantitative methodology was developed to identify protein interactions in a broad range of cell types by using FRET between fluorescent proteins. Genetic fusions of a target receptor to a FRET acceptor and a large library of candidate peptide ligands to a FRET donor enabled high-throughput optical screening for optimal interaction partners in the cytoplasm of Escherichia coli. Flow cytometric screening identified a panel of peptide ligands capable of recognizing the target receptors in the intracellular environment. For both SH3 and PDZ domain-type target receptors, physiologically meaningful consensus sequences were apparent among the isolated ligands. The relative dissociation constants of interacting partners could be measured directly by using a dilution series of cell lysates containing FRET hybrids, providing a previously undescribed high-throughput approach to rank the affinity of many interaction partners. FRET hybrid interaction screening provides a powerful tool to discover protein ligands in the cellular context with potential applications to a wide variety of eukaryotic cell types.cell sorting ͉ protein-ligand interactions T he ability to identify and quantitatively characterize proteinprotein interactions in living cells is essential for developing a detailed, system-level understanding of cellular function. The yeast two-hybrid (Y2H) system has served as the primary genetic tool to discover potential biological interaction partners for an enormous number of proteins (1, 2). Application of Y2H assays to each of the nearly 6,000 yeast ORFs enabled construction of the first large-scale protein interaction network in yeast (3, 4), and similar interaction studies were performed subsequently in Drosophila melanogaster and Caenorhabditis elegans (5, 6). Human-protein interaction networks are less well characterized and present difficult challenges to interaction mapping approaches. In fact, only a small fraction of an estimated 10 5 to 10 6 human-proteome interactions (7) have been unambiguously identified, primarily by using Y2H and mass spectrometry approaches (7,8). Unfortunately, high-throughput Y2H assays are typically prone to a high frequency of false positives that complicate the interpretation of interaction data. In some studies, it has been estimated that Ͼ50% of putative interactions identified are false positives (9).Several important challenges remain in the elucidation of protein-protein interaction networks and their influence on cell function (10). Large-scale interaction maps can portray basic network structure but lack quantitative features needed to understand network function. A predictive understanding of network function likely will require the elucidation of equilibrium and kinetic properties within a network, including individual equilibrium-binding constants. Furthermore, existing highthroughput approaches (e.g., Y2H) are not well suited to investigate real-time dynamics in protein networks essential for understanding cell function (11) because detection, in these cases, is ba...