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Assay Drug Dev Technol. 2003 Dec;1(6):811-22.

Measuring drug action in the cellular context using protein-fragment complementation assays.

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1
Odyssey Thera, San Ramon, CA 94583, USA.

Abstract

Cellular signal transduction occurs in the context of dynamic multiprotein complexes in highly ramified pathways. These complexes in turn interact with the cytoskeleton, protein scaffolds, membranes, lipid rafts, and specific subcellular organelles, contributing to the exquisitely tight regulation of their localization and activity. However, these realities of drug target biology are not addressed by currently available drug discovery platforms. In this article, we describe the use of protein-fragment complementation assays (PCAs) to assess drugs and drug targets in the context of their native environment. The PCA process allows for the detection of protein-protein complexes following the expression of full-length mammalian genes linked in-frame to polypeptide fragments of rationally dissected reporter genes. If cellular activity causes the association of two proteins linked to complementary reporter fragments, the interaction of the proteins of interest enables refolding of the fragments, which can then generate a quantifiable signal. Using a PCA based on a yellow fluorescent protein, we demonstrate that functional (p50/p65) complexes of the heterodimeric nuclear factor-kappaB transcription factor, as well as the transcription factor subunit p65 and its modulator IkappaBalpha, can be visualized and monitored in live cells. We observed similar responses of the PCA assays to the activities of the cognate endogenous proteins, including modulation by known agonists and antagonists. A proof-of-concept high throughput screen was carried out using the p50/p65 cell line, and potent inhibitors of this pathway were identified. These assays record the dynamic activity of signaling pathways in living cells and in real time, and validate the utility of PCA as a novel approach to drug discovery.

PMID:
15090227
DOI:
10.1089/154065803772613444
[Indexed for MEDLINE]
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