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Current strategies and progress for targeting the “undruggable” transcription factors

  
@article{APS10677,
	author = {Jing-jing Zhuang and Qian Liu and Da-lei Wu and Lu Tie},
	title = {Current strategies and progress for targeting the “undruggable” transcription factors},
	journal = {Acta Pharmacologica Sinica},
	volume = {43},
	number = {10},
	year = {2022},
	keywords = {},
	abstract = {Transcription factors (TFs) specifically bind to DNA, recruit cofactor proteins and modulate target gene expression, rendering them essential roles in the regulation of numerous biological processes. Meanwhile, mutated or dysregulated TFs are involved in a variety of human diseases. As multiple signaling pathways ultimately converge at TFs, targeting these TFs directly may prove to be more specific and cause fewer side effects, than targeting the upfront conventional targets in these pathways. All these features together endue TFs with great potential and high selectivity as therapeutic drug targets. However, TFs have been historically considered “undruggable”, mainly due to their lack of structural information, especially about the appropriate ligand-binding sites and protein- protein interactions, leading to relatively limited choices in the TF-targeting drug design. In this review, we summarize the recent progress of TF-targeting drugs and highlight certain strategies used for targeting TFs, with a number of representative drugs that have been approved or in the clinical trials as examples. Various approaches in targeting TFs directly or indirectly have been developed. Common direct strategies include aiming at defined binding pockets, proteolysis-targeting chimaera (PROTAC), and mutant protein reactivation. In contrast, the indirect ones comprise inhibition of protein-protein interactions between TF and other proteins, blockade of TF expression, targeting the post-translational modifications, and targeting the TF-DNA interactions. With more comprehensive structural information about TFs revealed by the powerful cryo-electron microscopy technology and predicted by machine-learning algorithms, plus more efficient compound screening platforms and a deeper understanding of TF-disease relationships, the development of TF-targeting drugs will certainly be accelerated in the near future.},
	issn = {1745-7254},	url = {http://www.chinaphar.com/article/view/10677}
}