Chrome Extension
WeChat Mini Program
Use on ChatGLM

Discovery of a 1,6-Naphthyridin-4-one-based AXL Inhibitor with Improved Pharmacokinetics and Enhanced in Vivo Antitumor Efficacy

European Journal of Medicinal Chemistry(2023)

Chinese Acad Sci | Univ Chinese Acad Sci

Cited 1|Views27
Abstract
The receptor tyrosine kinase AXL has emerged as an attractive target in anticancer drug discovery. Herein, we described the discovery of a new series of 1,6-naphthyridin-4-one derivatives as potent AXL inhibitors. Starting from a low in vivo potency compound 9 which was previously reported by our group, we utilized structure-based drug design and scaffold hopping strategies to discover potent AXL inhibitors. The privileged compound 13c was a highly potent and orally bioavailable AXL inhibitor with an IC50 value of 3.2 ± 0.3 nM. Compound 13c exhibited significantly improved in vivo antitumor efficacy in AXL-driven tumor xenograft mice, causing tumor regression at well-tolerated dose, and demonstrated favorable pharmacokinetic properties (MRT = 16.5 h, AUC0-∞ = 59,815 ng h/mL) in Sprague-Dawley rats. These results suggest that 13c is a promising therapeutic candidate for AXL-targeting cancer treatment.
More
Translated text
Key words
AXL inhibitor,In vivo antitumor efficacy,6-Naphthyridin-4-one derivatives,Scaffold hopping,Structure-based drug design
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
Related Papers
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

要点】:该论文描述了通过结构基于药物设计和骨架跳跃策略发现的一种新型1,6-萘啶-4-酮衍生物系列作为AXL抑制剂,其中优选化合物13c具有高potency和口服生物利用度,并且在AXL驱动的肿瘤异种移植小鼠中显示出显著增强的体内抗肿瘤疗效。

方法】:采用结构-基于药物设计和骨架跳跃策略。

实验】:实验在SD大鼠中进行,使用优选化合物13c,结果显示其具有良好的药代动力学特性,并对AXL驱动的肿瘤异种移植小鼠模型具有显著的体内抗肿瘤疗效。IC50值为3.2 ± 0.3 nM,中位存活时间(MRT)为16.5小时,area under the curve (AUC0 infinity)为59,815 ng h/mL。