Agonist Discovery for Membrane Proteins on Live Cells by Using DNA-encoded Libraries

Identifying biologically active ligands for membrane proteins is an important task in chemical biology. We report an approach to directly identify small molecule agonists against membrane proteins by selecting DNA-encoded libraries (DELs) on live cells. This method connects extracellular ligand binding with intracellular biochemical transformation, thereby biasing the selection toward agonist identification. We have demonstrated the methodology with three membrane proteins: epidermal growth factor receptor (EGFR), thrombopoietin receptor (TPOR), and insulin receptor (INSR). A ∼30 million and a 1.033 billion-compound DEL were selected against these targets, and novel agonists with subnanomolar affinity and low micromolar cellular activities have been discovered. The INSR agonists activated the receptor by possibly binding to an allosteric site, exhibited clear synergistic effects with insulin, and activated the downstream signaling pathways. Notably, the agonists did not activate the insulin-like growth factor 1 receptor (IGF-1R), a highly homologous receptor whose activation may lead to tumor progression. Collectively, this work has developed an approach toward "functional" DEL selections on the cell surface and may provide a widely applicable method for agonist discovery for membrane proteins.

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Publication Details

Journal
Journal of the American Chemical Society
Published
2024-08-22
DOI
https://doi.org/10.1021/jacs.4c08624
Citations
21
Primary Topic
Monoclonal and Polyclonal Antibodies Research
Type
article
Field-Weighted Citation Impact
8.49

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article

Agonist Discovery for Membrane Proteins on Live Cells by Using DNA-encoded Libraries

Yu Zhou, Xun He, Rui Hou, Yiran Huang et al.
21 citations
Journal of the American Chemical Society
Monoclonal and Polyclonal Antibodies Research
8.49
article

Agonist Discovery for Membrane Proteins on Live Cells by Using DNA-encoded Libraries

Yu Zhou, Xun He, Rui Hou, Yiran Huang, Feng Xiong, Dongyao Wang, Fong Sang Lam, Gang Li, Xiaoyu Li, Yan Cao, Yunxuan Jia
article en
21 citations

Abstract

Identifying biologically active ligands for membrane proteins is an important task in chemical biology. We report an approach to directly identify small molecule agonists against membrane proteins by selecting DNA-encoded libraries (DELs) on live cells. This method connects extracellular ligand binding with intracellular biochemical transformation, thereby biasing the selection toward agonist identification. We have demonstrated the methodology with three membrane proteins: epidermal growth factor receptor (EGFR), thrombopoietin receptor (TPOR), and insulin receptor (INSR). A ∼30 million and a 1.033 billion-compound DEL were selected against these targets, and novel agonists with subnanomolar affinity and low micromolar cellular activities have been discovered. The INSR agonists activated the receptor by possibly binding to an allosteric site, exhibited clear synergistic effects with insulin, and activated the downstream signaling pathways. Notably, the agonists did not activate the insulin-like growth factor 1 receptor (IGF-1R), a highly homologous receptor whose activation may lead to tumor progression. Collectively, this work has developed an approach toward "functional" DEL selections on the cell surface and may provide a widely applicable method for agonist discovery for membrane proteins.

Journal of the American Chemical SocietyVol. 146(35)
Second Military Medical University (CN), Lifetech Scientific (China) (CN), Shenzhen Bay Laboratory (CN), State Key Laboratory of Synthetic Chemistry (CN), Innovation and Technology Commission (HK), University of Hong Kong (HK)
National Natural Science Foundation of China, Research Grants Council, University Grants Committee, Science and Technology Commission of Shanghai Municipality, Innovation and Technology Commission, Shenzhen Bay Laboratory, Basic and Applied Basic Research Foundation of Guangdong Province
Zero hunger
Openalex Percentile: Top 2%
Monoclonal and Polyclonal Antibodies Research
8.49
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