Neutron encoded activity based probes

基于中子编码活动的探针

基本信息

批准号：
10402917
负责人：
Damian Winston Young
金额：
$ 42.95万
依托单位：
BAYLOR COLLEGE OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-01 至 2025-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10402917
关键词：
Amino Acids Area Bar Codes Basic Science Binding Biochemical Pathway Biological Catalogs Cell Line Cells Chemicals Chromatin Clinical Collection Data Analyses Defect Detection Development Disease Drug Design Drug Targeting Elements Enzymes Generations Histone Acetylation Histone Deacetylase Histone Deacetylase Inhibitor Isotopes Lead Libraries Life Ligation Malignant Neoplasms Mass Spectrum Analysis Measures Metabolic Methodology Methods Molecular Mechanisms of Action Neutrons Nuclear Pattern Pharmaceutical Preparations Pharmacology Photoaffinity Labels Physiological Piperazines Process Proteins Proteome Reaction Reagent Regulation Resistance Resolution Sampling Savings Site Specificity Statistical Data Interpretation Structure Support Groups System Systems Analysis Technology Testing Toxic effect Treatment Efficacy Work base blind candidate selection clinical application combinatorial design drug candidate drug development drug discovery high throughput screening in vivo inhibitor innovation novel novel drug class scaffold side effect small molecule small molecule inhibitor success

项目摘要

Drugs are designed to modulate the function of a critical protein involved in a disease; however, almost all small molecules have off-targets which can mitigate or altogether terminate their therapeutic efficacy. Unfortunately, there are no general methods that can identify all the protein targets that a drug binds to in an unbiased manner. For example, Histone Deacetylase Inhibitors (HDACIs) show promising clinical activity in many diseases; however, they are generally of low to moderate specificity and may act in part through, or be hindered by, uncharacterized off-target interactions. We propose a strategy that will allow for rapid and deep pharmacological profiling of early drug candidates that 1) identifies protein targets with extraordinary confidence, 2) localizes the precise site of interaction often with amino acid residue specificity, 3) is robust against metabolic alterations, 4) distinguishes the pharmacology of metabolites, 5) quantitates differences in pharmacological activity between cellular contexts. With this approach we will quantitate all interactions that each inhibitor has with proteins in a living cell. An neutron-encoded ‘bar code’ is added to activity-based probes during a click capture and release that allows us to blindly trace the drug in a nominal mass independent manner and simultaneously introduce quantitation channels. The barcodes are revealed in the isotopic fine structure by high resolution mass spectrometry yet do not compromise sensitivity at lower resolution fragmentation spectra. The neutron bar code is implemented by moving neutrons between elements and results in a prescribed pattern of relativistic nuclear mass defects embedded in the framework of a small molecule. With this method we can confidently retrieve drug-protein reaction products from in vivo systems regardless of metabolic alterations to the HDAC inhibitors, measure a pharmacological profile and determine molecular mechanism of action. Our central hypothesis is that neutron encoded activity based probe pharmacological profiling combined with innovative fragment-based discovery to generate selective HDACIs will enable the generation of a library of highly characterized and diversely selective HDACI probes. This will be realized through three specific aims: in aim 1 we will employ a novel and systematically diverse group of sp3-enriched fragments to generate HDACIs that sample the rim region of HDACs leading to highly selective interactions. In aim 2 we will measure the pharmacological profile of our novel HDACi’s and their effect on histone acetylation. In aim 3, we will develop a multiplexed barcoding system which to enable higher detection and resolution of drug targets over the entire proteome. This overcomes many challenges universal to early stage drug development efforts that have frustrated the development of specific HDAC inhibitors in particular. Although HDACIs will be the general focus of this proposal our method is general for drug development in any area.

药物旨在调节与疾病相关的关键蛋白质的功能，但几乎都是小蛋白质。不幸的是，分子的脱靶可能会减轻或完全终止其治疗效果。没有通用方法能够以公正的方式识别药物结合的所有蛋白质靶点。例如，组蛋白脱乙酰酶抑制剂（HDACIs）在许多疾病中显示出有前景的临床活性；然而，它们通常具有低到中等的特异性，并且可能部分通过以下方式发挥作用，或受到以下因素的阻碍：我们提出了一种能够实现快速、深入的互动的策略。早期候选药物的药理学分析表明 1) 蛋白质具有非凡的识别靶点置信度，2) 通常具有氨基酸残基特异性来定位相互作用的精确位点，3) 对代谢改变，4) 区分代谢物的药理学，5) 定量差异通过这种方法，我们将量化所有相互作用。每个抑制剂都与活细胞中的蛋白质一起添加到基于活性的中子编码“条形码”中。在点击捕获和释放过程中进行探针，使我们能够以独立的标称质量盲目地追踪药物方式并同时引入定量通道，条形码在同位素细粒中显示。通过高分辨率质谱分析结构，但不会影响较低分辨率下的灵敏度中子条形码是通过在元素和结果之间移动中子来实现的。嵌入小分子框架中的相对论核质量缺陷的规定模式。通过这种方法，我们可以自信地从体内系统中检索药物-蛋白质反应产物，无论 HDAC 抑制剂的代谢改变、测量药理学特征并确定分子我们的中心假设是基于中子编码活性的探针药理学。分析与基于片段的创新发现相结合以生成选择性 HDACIs 将使生成高度特征化和多样化选择性的 HDACI 探针库，这将通过以下方式实现。三个具体目标：在目标 1 中，我们将采用一组新颖且系统多样化的 sp3 富集片段生成 HDACI，对 HDAC 的边缘区域进行采样，从而产生高度选择性的相互作用。将测量我们的新型 HDACi 的药理学特征及其对组蛋白乙酰化的影响。在目标 3 中，我们将开发一种多重条形码系统，以实现更高的药物靶点检测和分辨率这克服了早期药物开发中普遍存在的许多挑战。尽管HDACIs已经挫败了特定HDAC抑制剂的开发努力。将是本提案的总体重点，我们的方法适用于任何领域的药物开发。