A platform to identify in vivo targets of covalent cancer drugs in 3D tissues

识别 3D 组织中共价癌症药物体内靶标的平台

• 批准号: 10714543
• 负责人: BENJAMIN F CRAVATT
• 金额: $ 45.07万
• 依托单位: SCRIPPS RESEARCH INSTITUTE, THE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-19 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10714543
• 关键词: 3-Dimensional; Acceleration; Adopted; Affinity; Agammaglobulinaemia tyrosine kinase; Animals; Antineoplastic Agents; Aspirin; Binding; Brain; Cardiotoxicity; Cardiovascular system; Cells; Chemicals; Chemistry; Clinical; Communities; Data; Development; Dose; Drug Targeting; Drug or chemical Tissue Distribution; Drug toxicity; Ensure; Enzyme Inhibitor Drugs; Enzymes; Epidermal Growth Factor Receptor; FAAH inhibitor; Fibroblast Growth Factor Receptors; Fluorescence; Foundations; Fright; Future; Goals; Heart; Histologic; Human; Hybrids; Image; In Situ; JAK3 gene; KRAS2 gene; Knowledge; Label; Link; Malignant Neoplasms; Mammals; Maps; Methods; Modeling; Molecular; Mus; Nature; Neurons; Oncogenic; Oncology; Organ; Organism; Penicillins; Persons; Pharmaceutical Preparations; Phosphotransferases; Positron-Emission Tomography; Prognosis; Proteins; Proteomics; Protocols documentation; Recording of previous events; Resolution; Signal Transduction; Specificity; Structure; Structure-Activity Relationship; Techniques; Technology; Therapeutic Index; Thinness; Tissue imaging; Tissues; Toxic effect; Translations; Tyrosine Kinase Inhibitor; body system; bropirimine; cancer therapy; cell type; cellular targeting; chemoproteomics; data streams; design; drug discovery; falls; high resolution imaging; imaging approach; imaging modality; in vivo; in vivo imaging; inhibitor; interest; kinase inhibitor; lead optimization; preference; programs; scale up; screening; side effect; small molecule; success; technology development; tool; whole body imaging

Abstract Covalent inhibitors represent some of the most successful drugs in human history, including aspirin and penicillin. Recently, targeted covalent drugs have taken center stage as a compelling approach for achieving major goals in oncology that have proven elusive for more classical reversible small molecules, including, for instance, the selective inactivation of oncogenic kinases (BTK, EGFR, FGFR, JAK3) and, most notably, the inhibition of the once-deemed undruggable KRAS protein. We are now in the midst of a resurgence of interest in covalent drugs for their demonstrated capability to engage cancer targets that have been historically considered undruggable. However, despite their proven success and inherent advantages of potency, there has been a general reluctance to develop covalent drugs due to the concern of potential irreversible off-target toxicity across different organ systems. Hence, a comprehensive understanding of both on and off-targets in vivo is critical for covalent drugs. Currently, it is impossible to determine drug binding across a whole animal with cellular and molecular resolution in mammals. Building upon a recent breakthrough in tissue imaging termed CATCH (Clearing-Assisted Tissue click Chemistry), we propose to develop a general platform for in vivo imaging of drug-target interactions with unprecedented spatial precision by integrated applications of high-resolution whole-body imaging and chemoproteomics (such as Activity-Based Proteomic Profiling, or ABPP) through the same covalent probes. This way, every cell in a living mammal targeted by the drug (both on- and off-target) can be revealed in situ and registered onto a defined protein map to screen and identify in vivo drug targets. The data stream generated by this platform could rapidly link the rich knowledge of drug affinity to the therapeutic index, therefore accelerating the translation of chemical activities into cancer therapies. Our team has well-established and complementary expertise in chemoproteomics and tissue imaging to ensure the successful execution of the project. In this IMAT R33 application, we plan to further develop CATCH to profile in vivo targets of covalent kinase inhibitors. First, we will adapt CATCH to 3D somatic tissues (Aim 1). Next, we will expand CATCH to an array of covalent BTK (Bruton’s tyrosine kinase) inhibitors (Aim 2). Finally, we will profile dose-dependent in vivo cellular targets of BTK inhibitors in the mouse cardiovascular system (Aim 3). We anticipate that these studies will establish in vivo CATCH methods for identifying targets of covalent BTK inhibitors to better understand their efficacy and toxicity. More generally, the established platform can be broadly applied to any covalent cancer drug for unbiased in vivo target identification. The pipeline, analytics, and high-resolution drug target data will be rapidly disseminated for public access and exploration, releasing an immediate, direct, and profound impact on covalent cancer drug discovery and refinement.

抽象的 共价抑制剂代表了人类历史上最成功的药物，包括阿司匹林和 青霉素。最近，有针对性的共价药物已成为中心阶段，作为实现的令人信服的方法 肿瘤学的主要目标已证明具有更古典的可逆小分子的弹性，包括 实例，致癌激酶的选择性失活（BTK，EGFR，FGFR，JAK3），最值得注意的是 抑制曾经含量的不良KRAS蛋白。我们现在正处于兴趣的复兴之中 在共价药物中，它们证明了参与历史上癌症靶标的能力 被认为是不可能的。但是，尽管他们证明了成功并继承了效力的优势，但 由于关注潜在的不可逆脱靶，一直不愿开发共价药物 跨不同器官系统的毒性。因此，对启动和关键目标的全面理解 体内对于共价药物至关重要。目前，无法确定整个动物的药物结合 哺乳动物中的细胞和分子分辨率。 基于最近在组织成像中的突破所谓的捕获的基础（清除辅助组织单击 化学），我们建议开发一个通用平台，用于与药物目标相互作用的体内成像 高分辨率全身成像的集成应用和 化学蛋白质组学（例如基于活性的蛋白质组学分析或ABPP）通过相同的共价问题。 这样，可以在原位揭示由药物靶向的活哺乳动物中的每个细胞 并注册到定义的蛋白质图上，以筛选并识别体内药物靶标。数据流 该平台产生的可能会迅速将药物亲和力的丰富知识与治疗指数联系起来 因此，将化学活动转化为癌症疗法。 我们的团队在化学蛋白质组学和组织成像方面拥有良好的和互补的专业知识 确保成功执行项目。在此IMAT R33应用程序中，我们计划进一步开发 捕获共价激酶抑制剂的体内靶标。首先，我们将调整捕获到3D体细胞组织 （目标1）。接下来，我们将扩展到一系列共价BTK（布鲁顿的酪氨酸激酶）抑制剂（AIM 2）。 最后，我们将介绍小鼠心血管中BTK抑制剂的剂量依赖性体内细胞靶标 系统（目标3）。我们预计这些研究将建立体内捕获方法，以识别 共价BTK抑制剂可以更好地了解其效率和毒性。更一般地，已建立的平台 可以广泛地应用于任何共价癌症药物，以实现无偏的体内靶标识别。管道， 分析和高分辨率药物目标数据将迅速传播以进行公众访问和探索， 对共价癌症药物发现和精致产生直接，直接和深远的影响。