Time-resolved FRET-based allostery sensors for any protein kinase drug target

适用于任何蛋白激酶药物靶标的时间分辨 FRET 变构传感器

• 批准号: 9887709
• 负责人: Nicholas Mark Levinson
• 金额: $ 37.55万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9887709
• 关键词: Active Sites; Affinity; Allosteric Site; Antineoplastic Agents; Architecture; Area; Benchmarking; Binding; Biological Assay; CCNE1 gene; Cancer Patient; Chemicals; Chemistry; Clinical; Complex; Crowding; Custom; Cyclin-Dependent Kinase Inhibitor; Cysteine; Development; Disease; Dissociation; Drug Screening; Drug Targeting; Dyes; Employment; Excision; FGFR1 gene; Failure; Fluorescence; Fluorescence Resonance Energy Transfer; Fluorescent Probes; Funding; Growth; High Prevalence; Human; Incidence; Kinetics; Label; Legal patent; Malignant Neoplasms; Malignant neoplasm of prostate; Mediating; Mitotic; Monitor; Movement; Neuroblastoma; Neurosecretory Systems; Phosphotransferases; Play; Procedures; Protein Kinase; Proto-Oncogene Proteins B-raf; Publishing; Reader; Readiness; Resistance; Resolution; Series; Signal Transduction; Site; Structure; Sulfhydryl Compounds; System; Technology; Therapeutic; Time; Toxic effect; Treatment Failure; Work; aurora kinase A; base; cancer therapy; combat; design; drug development; drug discovery; high throughput screening; inhibitor/antagonist; kinase inhibitor; nanosecond; new technology; next generation; novel; novel anticancer drug; novel strategies; overexpression; protein complex; scaffold; screening; screening program; sensor; sensor technology; small molecule; src-Family Kinases; success; tool; unnatural amino acids

ABSTRACT The protein kinases are the top class of drug targets for the development of new cancer therapeutics. Existing kinase inhibitors, which target the highly-conserved active sites of kinases, have major limitations including poor selectivity and a high incidence of clinical resistance leading to treatment failure. New allosteric inhibitors, which bind in other pockets outside the kinase active site and trigger structural changes that block kinase activity, are far more selective and are highly effective at overriding clinical resistance to conventional kinase inhibitors. However, allosteric kinase inhibitors have proven extremely challenging to identify with existing drug screening technologies, and are only available for a small handful of kinases. A major reason for this failure of existing drug screening technologies is that they cannot detect the atomic- scale structural changes that define the mode of action of allosteric kinase inhibitors. We have developed a game-changing high-throughput screening technology, based on nanosecond time-resolved fluorescence, that can identify allosteric inhibitors by tracking with atomic resolution the structural changes they trigger in the kinase drug target. Applying this technology to the mitotic protein kinase Aurora A, we have shown that it can simultaneously track inhibitor binding affinity and allosteric effects on the kinase, can classify inhibitors into different allosteric subtypes, and is sufficiently accurate, rapid and scalable to handle high-throughput screening projects. To maximize the impact of the technology on the drug discovery pipeline, several technical barriers need to be surmounted to expand the scope of the technology beyond the current single drug target Aurora A. Our current technology is based on a chemical labeling procedure for incorporating fluorescent probes, cysteine labeling, that is not readily applicable to many important kinase drug targets due to the presence of cysteine residues important for structural integrity and catalytic function. In this proposal, we broaden the scope of the technology to make it applicable to the majority of the ~500 human kinases by developing a series of new tools for site-specific probe incorporation and by expanding the range and type of small molecules that can be identified in screening. Finally, we benchmark the suitability of the technology for real-world drug discovery efforts by performing a high-throughput screening project to identify novel allosteric inhibitors of at least one protein kinase for which no allosteric inhibitors are currently available. The success of this project will bring an entirely-new allosteric drug discovery technology into being, with unique capabilities that no existing technology can provide. Employment of this approach could jumpstart the discovery of allosteric kinase inhibitors for a large number of important cancer drug targets, broadening the range of therapeutic options for cancer patients and providing a much-needed new approach for combating the high prevalence of clinical resistance to first-line kinase inhibitor therapies.

抽象的 蛋白激酶是开发新癌症疗法的顶级药物靶点。现存的 激酶抑制剂针对激酶高度保守的活性位点，具有主要局限性，包括效果差 选择性和临床耐药性的高发生率导致治疗失败。新的变构抑制剂， 结合在激酶活性位点外的其他口袋中并触发阻止激酶活性的结构变化， 选择性更强，并且在克服对传统激酶抑制剂的临床耐药性方面非常有效。 然而，事实证明，通过现有的药物筛选来识别变构激酶抑制剂极具挑战性 技术，并且仅适用于少数激酶。 现有药物筛选技术失败的一个主要原因是它们无法检测原子 规模结构变化定义了变构激酶抑制剂的作用模式。我们开发了一个 改变游戏规则的高通量筛选技术，基于纳秒时间分辨荧光， 可以通过原子分辨率追踪变构抑制剂在激酶中引发的结构变化来识别变构抑制剂 药物靶点。将此技术应用于有丝分裂蛋白激酶 Aurora A，我们已经证明它可以 同时追踪抑制剂的结合亲和力和对激酶的变构效应，可以将抑制剂分类为 不同的变构亚型，并且足够准确、快速且可扩展以处理高通量筛选 项目。为了最大限度地发挥该技术对药物发现管道的影响，需要克服几个技术障碍 需要克服这些挑战才能将技术范围扩大到目前单一药物靶点 Aurora A 之外。 我们当前的技术基于结合荧光探针的化学标记程序， 半胱氨酸标记，由于存在 半胱氨酸残基对于结构完整性和催化功能很重要。在本提案中，我们扩大了范围 通过开发一系列新的技术，使其适用于约 500 种人类激酶中的大多数 用于位点特异性探针掺入的工具，并通过扩展可以的小分子的范围和类型 筛查中发现的。最后，我们对该技术在现实世界药物发现工作中的适用性进行了基准测试 通过进行高通量筛选项目来鉴定至少一种蛋白质的新型变构抑制剂 目前尚无变构抑制剂可用的激酶。 该项目的成功将带来全新的变构药物发现技术， 现有技术无法提供的独特功能。采用这种方法可以快速启动 发现大量重要癌症药物靶点的变构激酶抑制剂，拓宽了范围 为癌症患者提供了多种治疗选择，并提供了一种急需的对抗高风险的新方法 对一线激酶抑制剂治疗的临床耐药性的普遍存在。