WeChat Mini Program
Old Version Features

Site-selective Structural Modification of Toosendanin Enables One-Step Synthesis of 12-Hydroxyamoorastatin: A Natural Tautomeric Antitumor Lead with Low Toxicity.

Qing-Yan Cheng, Chen Yang, Yu-Ting Liao, Shu-Chao Yang, Hong-Yuan Wang, Bing-Jie Zhou,Dashan Li, Wen-Jing Wang, Dao-Feng Chen,Li-Dong Shao

Bioorganic chemistry(2025)

Cited 0|Views1
Abstract
Natural limonoid triterpenoids toosendanin (1) and 12-hydroxyamoorastatin (5) have been reported to possess broad-spectrum antitumor activity. However, development of antitumor drugs for the treatment of 1 has reached an impasse, due to its severe hepatotoxicity. Notably, compound 5 is a C-12 deacetylated product of 1, but scholars have studied and exploited 5 much less than 1 especially on antitumor activity and toxicity, of which the resource scarcity and structural ambiguity of 5 may be great hindrances. To address these concerns, a site-selective modification of 1 was developed, in which C-12 deacetylation with LiHMDS enabled the one-step synthesis of 5 from 1, solving its insufficient resources. We then revised the 5/7-tautomerization to C-12/C-29-tautomerization of HAR (5) by extensive NMR, LC-MS, DFT-calculations, and X-ray analyses, and determined the relative content of the tautomers in solution phase. Moreover, the biological evaluation of the synthesized derivatives prompted identification of 5 as a natural lead with better antitumor activities in vitro/in vivo. Namely, 5 exhibited antitumor activity through multiple mechanisms, including inhibition of DDR repair, down-regulation of the DNA damage stress-associated transcription factor HSF-1 and its downstream HSPs, promotion of synthetic lethality, disruption of the BAX/BCL2 homeostasis, and elicitation of cellular autophagy. Crucially, 5 achieved 62 % TGI (vs. 17 % for 1) in the JIMT-1 xenograft tumor models without exhibiting hepatotoxicity, providing a solid support to the development of natural limonoid antitumor lead.
More
Translated text
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined