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设计具有优异疗效且无全身毒性的 BET 抑制剂瓶刷前药。

Design of BET Inhibitor Bottlebrush Prodrugs with Superior Efficacy and Devoid of Systemic Toxicities.

机构信息

Department of Chemistry, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.

XTuit Pharmaceuticals, 35 Gatehouse Drive, Waltham, Massachusetts 02451, United States.

出版信息

J Am Chem Soc. 2021 Mar 31;143(12):4714-4724. doi: 10.1021/jacs.1c00312. Epub 2021 Mar 19.

Abstract

Prodrugs engineered for preferential activation in diseased versus normal tissues offer immense potential to improve the therapeutic indexes (TIs) of preclinical and clinical-stage active pharmaceutical ingredients that either cannot be developed otherwise or whose efficacy or tolerability it is highly desirable to improve. Such approaches, however, often suffer from trial-and-error design, precluding predictive synthesis and optimization. Here, using bromodomain and extra-terminal (BET) protein inhibitors (BETi)-a class of epigenetic regulators with proven anticancer potential but clinical development hindered in large part by narrow TIs-we introduce a macromolecular prodrug platform that overcomes these challenges. Through tuning of traceless linkers appended to a "bottlebrush prodrug" scaffold, we demonstrate correlation of prodrug activation kinetics with tumor pharmacokinetics, enabling the predictive design of novel BETi prodrugs with enhanced antitumor efficacies and devoid of dose-limiting toxicities in a syngeneic triple-negative breast cancer murine model. This work may have immediate clinical implications, introducing a platform for predictive prodrug design and potentially overcoming hurdles in drug development.

摘要

前药设计用于在疾病组织与正常组织中优先激活,为改善临床前和临床阶段活性药物成分的治疗指数(TI)提供了巨大的潜力,这些成分要么无法开发,要么其疗效或耐受性需要极大改善。然而,这些方法往往受到反复试验的设计限制,无法进行预测性的合成和优化。在这里,我们使用溴结构域和末端结构域(BET)蛋白抑制剂(BETi)-一类具有明确抗癌潜力的表观遗传调节剂,但由于 TI 较窄,在很大程度上阻碍了其临床开发-引入了一种大分子前药平台,克服了这些挑战。通过调整连接到“瓶刷前药”支架上的无痕迹接头,我们证明了前药激活动力学与肿瘤药代动力学之间的相关性,从而能够在同种异体三阴性乳腺癌小鼠模型中,预测设计具有增强抗肿瘤功效且无剂量限制毒性的新型 BETi 前药。这项工作可能具有直接的临床意义,为预测性前药设计引入了一个平台,并可能克服药物开发中的障碍。

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