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基于数据驱动的控制多靶性抗肿瘤药物的构建。

Data-Driven Construction of Antitumor Agents with Controlled Polypharmacology.

机构信息

Center for Integrative Chemical Biology and Drug Discovery, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy , University of North Carolina at Chapel Hill , Chapel Hill , North Carolina 27599-7363 , United States.

Aflac Cancer and Blood Disorders Center, Children's Healthcare of Atlanta, and Department of Pediatrics , Emory University , Atlanta , Georgia 30322 , United States.

出版信息

J Am Chem Soc. 2019 Oct 2;141(39):15700-15709. doi: 10.1021/jacs.9b08660. Epub 2019 Sep 20.

Abstract

Controlling which particular members of a large protein family are targeted by a drug is key to achieving a desired therapeutic response. In this study, we report a rational data-driven strategy for achieving restricted polypharmacology in the design of antitumor agents selectively targeting the TYRO3, AXL, and MERTK (TAM) family tyrosine kinases. Our computational approach, based on the concept of fragments in structural environments (FRASE), distills relevant chemical information from structural and chemogenomic databases to assemble a three-dimensional inhibitor structure directly in the protein pocket. Target engagement by the inhibitors designed led to disruption of oncogenic phenotypes as demonstrated in enzymatic assays and in a panel of cancer cell lines, including acute lymphoblastic and myeloid leukemia (ALL/AML) and nonsmall cell lung cancer (NSCLC). Structural rationale underlying the approach was corroborated by X-ray crystallography. The lead compound demonstrated potent target inhibition in a pharmacodynamic study in leukemic mice.

摘要

控制药物靶向的大型蛋白质家族中的特定成员是实现理想治疗反应的关键。在这项研究中,我们报告了一种合理的数据驱动策略,用于在设计选择性靶向 TYRO3、AXL 和 MERTK(TAM)家族酪氨酸激酶的抗肿瘤药物时实现受限的多药理学。我们的计算方法基于结构环境中的片段概念(FRASE),从结构和化学生物基因组学数据库中提取相关化学信息,直接在蛋白质口袋中组装三维抑制剂结构。设计的抑制剂的靶标结合导致致癌表型的破坏,如酶测定和一系列癌细胞系(包括急性淋巴细胞白血病和髓样白血病(ALL/AML)和非小细胞肺癌(NSCLC))中所证明的那样。该方法的结构原理得到了 X 射线晶体学的证实。在白血病小鼠的药效学研究中,先导化合物表现出很强的靶标抑制作用。

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