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使用DNA编程亲和标记法鉴定激酶抑制剂阿利西替尼(MLN8237)的靶点

Target Identification of Kinase Inhibitor Alisertib (MLN8237) by Using DNA-Programmed Affinity Labeling.

作者信息

Wang Dong-Yao, Cao Yan, Zheng Le-Yi, Chen Lang-Dong, Chen Xiao-Fei, Hong Zhan-Ying, Zhu Zhen-Yu, Li Xiaoyu, Chai Yi-Feng

机构信息

School of Pharmacy, Second Military Medical University, No. 325 Guohe Road, Shanghai, 200433, P.R. China.

Department of Chemistry, The University of Hong Kong, Pokfulam Road, Hong Kong, SAR China.

出版信息

Chemistry. 2017 Aug 10;23(45):10906-10914. doi: 10.1002/chem.201702033. Epub 2017 Jul 26.

Abstract

Accurate identification of the molecular targets of bioactive small molecules is a highly important yet challenging task in biomedical research. Previously, a method named DPAL (DNA-programmed affinity labeling) for labeling and identifying the cellular targets of small molecules and nucleic acids was developed. Herein, DPAL is applied for the target identification of Alisertib (MLN8237), which is a highly specific aurora kinase A (AKA) inhibitor and a drug candidate being tested in clinical trials for cancer treatment. Apart from the well-established target of AKA, several potential new targets of MLN8237 were identified. Among them, p38 mitogen-activated protein kinase (p38) and laminin receptor (LAMR) were validated to be implicated in the anticancer activities of MLN8237. Interestingly, these new targets were not identified with non-DNA-based affinity probes. This work may facilitate an understanding of the molecular basis of the efficacy and side effects of MLN8237 as a clinical drug candidate. On the other hand, this work has also demonstrated that the method of DPAL could be a useful tool for target identification of bioactive small molecules.

摘要

在生物医学研究中,准确识别生物活性小分子的分子靶点是一项极其重要但又具有挑战性的任务。此前,开发了一种名为DPAL(DNA编程亲和标记)的方法,用于标记和识别小分子与核酸的细胞靶点。在此,DPAL被应用于阿利西替尼(MLN8237)的靶点识别,阿利西替尼是一种高度特异性的极光激酶A(AKA)抑制剂,也是一种正在癌症治疗临床试验中进行测试的候选药物。除了已明确的AKA靶点外,还识别出了MLN8237的几个潜在新靶点。其中,p38丝裂原活化蛋白激酶(p38)和层粘连蛋白受体(LAMR)被证实与MLN8237的抗癌活性有关。有趣的是,这些新靶点并未通过非基于DNA的亲和探针识别出来。这项工作可能有助于理解MLN8237作为临床候选药物的疗效和副作用的分子基础。另一方面,这项工作也证明了DPAL方法可能是一种用于生物活性小分子靶点识别的有用工具。

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