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Proteome-scale binary interactomics in human cells

(2016) MOLECULAR & CELLULAR PROTEOMICS. 15(12). p.3624-3639
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Abstract
Because proteins are the main mediators of most cellular processes they are also prime therapeutic targets. Identifying physical links among proteins and between drugs and their protein targets is essential in order to understand the mechanisms through which both proteins themselves and the molecules they are targeted with act. Thus, there is a strong need for sensitive methods that enable mapping out these biomolecular interactions. Here we present a robust and sensitive approach to screen proteome-scale collections of proteins for binding to proteins or small molecules using the well validated MAPPIT (Mammalian Protein-Protein Interaction Trap) and MASPIT (Mammalian Small Molecule-Protein Interaction Trap) assays. Using high-density reverse transfected cell microarrays, a close to proteome-wide collection of human ORF clones can be screened for interactors at high throughput. The versatility of the platform is demonstrated through several examples. With MAPPIT, we screened a 15k ORF library for binding partners of RNF41, an E3 ubiquitin protein ligase implicated in receptor sorting, identifying known and novel interacting proteins. The potential related to the fact that MAPPIT operates in living human cells is illustrated in a screen where the protein collection is scanned for interactions with the glucocorticoid receptor (GR) in its unliganded versus dexamethasone-induced activated state. Several proteins were identified the interaction of which is modulated upon ligand binding to the GR, including a number of previously reported GR interactors. Finally, the screening technology also enables detecting small molecule target proteins, which in many drug discovery programs represents an important hurdle. We show the efficiency of MASPIT-based target profiling through screening with tamoxifen, a first-line breast cancer drug, and reversine, an investigational drug with interesting dedifferentiation and antitumor activity. In both cases, cell microarray screens yielded known and new potential drug targets highlighting the utility of the technology beyond fundamental biology.
Keywords
SMALL-MOLECULE, GLUCOCORTICOID-RECEPTOR, INTERACTION NETWORK, MAMMALIAN-CELLS, TARGET, DEGRADATION, EXPRESSION, TAMOXIFEN, REVERSINE, COMPLEX

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Citation

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Chicago
Lievens, Sam, José Van Der Heyden, Delphine Masschaele, Leentje De Ceuninck, Ioanna Petta, Surya Gupta, Veronic De Puysseleyr, et al. 2016. “Proteome-scale Binary Interactomics in Human Cells.” Molecular & Cellular Proteomics 15 (12): 3624–3639.
APA
Lievens, Sam, Van Der Heyden, J., Masschaele, D., De Ceuninck, L., Petta, I., Gupta, S., De Puysseleyr, V., et al. (2016). Proteome-scale binary interactomics in human cells. MOLECULAR & CELLULAR PROTEOMICS, 15(12), 3624–3639.
Vancouver
1.
Lievens S, Van Der Heyden J, Masschaele D, De Ceuninck L, Petta I, Gupta S, et al. Proteome-scale binary interactomics in human cells. MOLECULAR & CELLULAR PROTEOMICS. 2016;15(12):3624–39.
MLA
Lievens, Sam, José Van Der Heyden, Delphine Masschaele, et al. “Proteome-scale Binary Interactomics in Human Cells.” MOLECULAR & CELLULAR PROTEOMICS 15.12 (2016): 3624–3639. Print.
@article{8167638,
  abstract     = {Because proteins are the main mediators of most cellular processes they are also prime therapeutic targets. Identifying physical links among proteins and between drugs and their protein targets is essential in order to understand the mechanisms through which both proteins themselves and the molecules they are targeted with act. Thus, there is a strong need for sensitive methods that enable mapping out these biomolecular interactions. Here we present a robust and sensitive approach to screen proteome-scale collections of proteins for binding to proteins or small molecules using the well validated MAPPIT (Mammalian Protein-Protein Interaction Trap) and MASPIT (Mammalian Small Molecule-Protein Interaction Trap) assays. Using high-density reverse transfected cell microarrays, a close to proteome-wide collection of human ORF clones can be screened for interactors at high throughput. The versatility of the platform is demonstrated through several examples. With MAPPIT, we screened a 15k ORF library for binding partners of RNF41, an E3 ubiquitin protein ligase implicated in receptor sorting, identifying known and novel interacting proteins. The potential related to the fact that MAPPIT operates in living human cells is illustrated in a screen where the protein collection is scanned for interactions with the glucocorticoid receptor (GR) in its unliganded versus dexamethasone-induced activated state. Several proteins were identified the interaction of which is modulated upon ligand binding to the GR, including a number of previously reported GR interactors. Finally, the screening technology also enables detecting small molecule target proteins, which in many drug discovery programs represents an important hurdle. We show the efficiency of MASPIT-based target profiling through screening with tamoxifen, a first-line breast cancer drug, and reversine, an investigational drug with interesting dedifferentiation and antitumor activity. In both cases, cell microarray screens yielded known and new potential drug targets highlighting the utility of the technology beyond fundamental biology.},
  author       = {Lievens, Sam and Van Der Heyden, Jos{\'e} and Masschaele, Delphine and De Ceuninck, Leentje and Petta, Ioanna and Gupta, Surya and De Puysseleyr, Veronic and Vauthier, Virginie and Lemmens, Irma and De Clercq, Dries and Defever, Dieter and Vanderroost, Nele and De Smet, Ann-Sophie and Eyckerman, Sven and Van Calenbergh, Serge and Martens, Lennart and De Bosscher, Karolien and Libert, Claude and Hill, Davod E and Vidal, Marc and Tavernier, Jan},
  issn         = {1535-9476},
  journal      = {MOLECULAR \& CELLULAR PROTEOMICS},
  language     = {eng},
  number       = {12},
  pages        = {3624--3639},
  title        = {Proteome-scale binary interactomics in human cells},
  url          = {http://dx.doi.org/10.1074/mcp.M116.061994},
  volume       = {15},
  year         = {2016},
}

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