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.

摘要 共价抑制剂代表了人类历史上一些最成功的药物，包括阿司匹林和 青霉素。最近，靶向共价药物已经作为实现靶向治疗的一种引人注目的方法占据了中心舞台。 肿瘤学中的主要目标已被证明是更经典的可逆小分子难以实现的，包括， 例如，致癌激酶（BTK、EGFR、FGFR、JAK 3）的选择性失活，最值得注意的是， 抑制曾经被认为不可用的KRAS蛋白。我们现在正处于一个复苏的兴趣， 在共价药物中，它们被证明具有与癌症靶点结合的能力， 被认为是不可抵抗的然而，尽管它们已被证明是成功的，而且具有内在的效力优势， 由于担心潜在的不可逆脱靶， 不同器官系统的毒性。因此，全面了解在靶和脱靶， 体内对于共价药物至关重要。目前，不可能确定整个动物的药物结合 在哺乳动物中具有细胞和分子分辨率。 基于最近在组织成像方面的突破，称为CATCH（清除辅助组织点击 化学），我们建议开发一个通用平台，用于药物-靶标相互作用的体内成像， 通过高分辨率全身成像的综合应用实现前所未有的空间精度， 化学蛋白质组学（如基于活性的蛋白质组学分析，或ABPP）通过相同的共价探针。 通过这种方式，可以原位显示药物靶向的活哺乳动物中的每个细胞（包括靶向和脱靶） 并配准到确定的蛋白质图谱上以筛选和鉴定体内药物靶点。数据流 通过这个平台产生的可以快速地将药物亲和性的丰富知识与治疗指标联系起来， 从而加速化学活性转化为癌症治疗。 我们的团队在化学蛋白质组学和组织成像方面拥有完善和互补的专业知识， 确保项目的顺利实施。在这个IMAT R33应用中，我们计划进一步开发 CATCH分析共价激酶抑制剂的体内靶点。首先，我们将使CATCH适应3D体细胞组织 (Aim 1）。接下来，我们将CATCH扩展到共价BTK（布鲁顿酪氨酸激酶）抑制剂阵列（目标2）。 最后，我们将描述BTK抑制剂在小鼠心血管系统中的剂量依赖性体内细胞靶点。 系统（目标3）。我们预计这些研究将建立体内CATCH方法，用于识别靶点， 共价BTK抑制剂，以更好地了解其功效和毒性。更一般地说，现有平台 可广泛应用于任何共价抗癌药物的无偏体内靶点鉴定。管道， 分析和高分辨率药物靶点数据将迅速传播，供公众访问和探索， 对共价抗癌药物的发现和改进产生了即时、直接和深远的影响。