The AUTOTAC chemical biology platform for targeted protein degradation via the autophagy-lysosome system
- Authors
- Ji, Chang Hoon; Kim, Hee Yeon; Lee, Min Ju; Heo, Ah Jung; Park, Daniel Youngjae; Lim, Sungsu; Shin, Seul gi; Ganipisetti Srinivasrao; Yang, Woo Seung; Jung, Chang An; Kim, Kun Young; Jeong, Eun Hye; Park, Sun Ho; Bin Kim, Su; Lee, Su Jin; Na, Jeong Eun; Kang, Ji In; Chi, Hyung Min; Kim, Hyun Tae; Kim, Yun Kyung; Kim, Bo Yeon; Kwon, Yong Tae
- Issue Date
- 2022-02
- Publisher
- Nature Publishing Group
- Citation
- Nature Communications, v.13, no.1
- Abstract
- Targeted protein degradation allows targeting undruggable proteins for therapeutic applications as well as eliminating proteins of interest for research purposes. While several degraders that harness the proteasome or the lysosome have been developed, a technology that simultaneously degrades targets and accelerates cellular autophagic flux is still missing. In this study, we develop a general chemical tool and platform technology termed AUTOphagy-TArgeting Chimera (AUTOTAC), which employs bifunctional molecules composed of target-binding ligands linked to autophagy-targeting ligands. AUTOTACs bind the ZZ domain of the otherwise dormant autophagy receptor p62/Sequestosome-1/SQSTM1, which is activated into oligomeric bodies in complex with targets for their sequestration and degradation. We use AUTOTACs to degrade various oncoproteins and degradation-resistant aggregates in neurodegeneration at nanomolar DC50 values in vitro and in vivo. AUTOTAC provides a platform for selective proteolysis in basic research and drug development. Targeted protein degradation is a promising approach for basic research and therapeutic applications. Here, the authors develop a targeted protein degradation platform called AUTOTAC to degrade oncoproteins and neurodegeneration-associated proteins via the p62-dependent autophagy-lysosome system.
- Keywords
- PROTEOLYSIS; RECEPTOR; DEGRON; CANCER
- ISSN
- 2041-1723
- URI
- https://pubs.kist.re.kr/handle/201004/76793
- DOI
- 10.1038/s41467-022-28520-4
- Appears in Collections:
- KIST Article > 2022
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