Journal
CHEMBIOCHEM
Volume 23, Issue 16, Pages -Publisher
WILEY-V C H VERLAG GMBH
DOI: 10.1002/cbic.202200209
Keywords
bioorganic chemistry; chemically induced dimerization; heterobifunctional; protein-protein interactions; phase separation
Funding
- University of Pennsylvania
- National Institutes of Health [NIH R01-GM118510]
- National Science Foundation Faculty Early Career Development Program (NSF CAREER) [2145083]
- NIH [3R01GM118510-03S1, 3R01GM087605-06S1]
- Vagelos Institute for Energy Science and Technology
- Div Of Molecular and Cellular Bioscience
- Direct For Biological Sciences [2145083] Funding Source: National Science Foundation
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This research utilizes chemically induced dimerization tools to manipulate protein-protein interactions, synthesizes a chemical tool library with different linker structures, and visualizes dimerization in real time in live cells through quantitative microscopy. By optimizing the probes, the recruitment of POIs to different cellular locations is successfully demonstrated, and local and global phase separation are induced and monitored.
To mimic the levels of spatiotemporal control that exist in nature, tools for chemically induced dimerization (CID) are employed to manipulate protein-protein interactions. Although linker composition is known to influence speed and efficiency of heterobifunctional compounds, modeling or in vitro experiments are often insufficient to predict optimal linker structure. This can be attributed to the complexity of ternary complex formation and the overlapping factors that impact the effective concentration of probe within the cell, such as efflux and passive permeability. Herein, we synthesize a library of modular chemical tools with varying linker structures and perform quantitative microscopy in live cells to visualize dimerization in real-time. We use our optimized probe to demonstrate our ability to recruit a protein of interest (POI) to the mitochondria, cell membrane, and nucleus. Finally, we induce and monitor local and global phase separation. We highlight the importance of quantitative approaches to linker optimization for dynamic systems and introduce new, synthetically accessible tools for the rapid control of protein localization.
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