Harnessing Small Molecules to Probe the Structure and Function of Regulatory RNAs

利用小分子探测调节 RNA 的结构和功能

• 批准号: 10405219
• 负责人: Amanda E Hargrove
• 金额: $ 42.53万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-15 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10405219
• 关键词: 2019-nCoV; Automobile Driving; Bacterial Infections; Binding; Biological; Biological Assay; Biological Process; Biology; Cells; Chemicals; Complex; Development; Disease; Disseminated Malignant Neoplasm; Enterovirus 71; Explosion; HIV; Health; Human; Lead; Libraries; Ligands; Machine Learning; Methods; Molecular Biology; Molecular Conformation; Neuromuscular Diseases; Oncogenic; Pattern Recognition; Property; Proteins; Protocols documentation; Quantitative Structure-Activity Relationship; RNA; RNA Binding; RNA Conformation; RNA-targeting therapy; Research; Scientist; Structure; Techniques; Therapeutic; Translations; Untranslated RNA; Viral; Virus Diseases; Virus Replication; Work; bacterial resistance; base; human disease; improved; insight; interdisciplinary approach; interest; programs; scaffold; screening; small molecule; success; tool

PROJECT SUMMARY Despite the recent explosion of interest in RNA targeting, therapeutic potential is presently limited by a lack of fundamental understanding of how to achieve selective and functional small molecule targeting. The overarching focus of our research program is to elucidate the key drivers of selectivity in small molecule:RNA recognition and to apply these principles to facilitate development of RNA-targeted chemical probes and therapeutics that modulate RNA function. To begin, we identified physicochemical, structural, and spatial properties of biologically active RNA ligands that are distinct from those of protein-targeted ligands. Synthetic elaboration of RNA binding scaffolds into a library enriched with these properties has led to improved recognition of disease relevant RNA, including viral and long noncoding RNA structures. We used pattern recognition protocols to identify RNA topologies that can be differentially recognized by small molecules and have elaborated this technique to visualize conformational changes. This combined work has led to remarkable successes such as the targeting of enterovirus 71 RNA, where our ligand induced a dramatic conformation change that increased binding of a repressive human protein, decreased viral translation, and inhibited viral replication. Our approach is also showing preliminary success against SARS-CoV2 regulatory RNA. Building off these accomplishments, we propose to develop new libraries and screening methods to understand functional selectivity against a range of more complex tertiary and quaternary structures. Insights into the most critical driving factors will be revealed through pattern recognition / machine learning analysis as well as through an ensemble-based QSAR method that will allow rational targeting of any RNA. Key determinants of biological selectivity will be revealed in high throughput cell-based assays. These discoveries will be further enhanced by elucidation of the structure-dynamics-function relationships of oncogenic long noncoding RNAs. Our tools have lowered barriers to the discovery of selective RNA ligands. The proposed work will finally open a new horizon in RNA-targeting, in which chemical and biological scientists will readily and productively screen for small molecule probes against a wide range of RNA molecules, including those relevant to human disease. Such capabilities will allow the therapeutic potential of RNA to be fully exploited and inherently transform our understanding of molecular biology.

项目摘要 尽管最近对RNA靶向的兴趣爆炸了，但目前缺乏治疗潜力的限制 对如何实现选择性和功能性的小分子靶向的基本理解。总体 我们的研究计划的重点是阐明小分子中选择性的关键驱动因素：RNA识别和 应用这些原则以促进靶向RNA的化学探针和治疗剂的开发 调节RNA功能。首先，我们确定了生物学上的物理化学，结构和空间特性 活性RNA配体不同于靶向蛋白质的配体的配体。 RNA结合的合成阐述 脚手架进入具有这些特性的图书馆已导致对疾病相关的RNA的认识，从而提高 包括病毒和长的非编码RNA结构。我们使用模式识别方案来识别RNA 可以通过小分子差异识别的拓扑结构，并将这种技术阐述为 可视化构象变化。这项合并的工作导致了巨大的成功，例如目标 肠病毒71 RNA，我们的配体引起了急剧的构象变化，增加了A的结合 抑制性人蛋白，病毒翻译降低并抑制病毒复制。我们的方法也是 显示针对SARS-COV2调节RNA的初步成功。 在建立这些成就的基础上，我们建议开发新的图书馆和筛选方法以了解 功能选择性针对一系列更复杂的第三结构和第四纪结构。最深入的见解 关键的驱动因素将通过模式识别 /机器学习分析以及通过 基于整体的QSAR方法，将允许任何RNA的合理靶向。生物学的关键决定因素 选择性将在基于高吞吐量的细胞测定中揭示。这些发现将通过 阐明致癌性长的非编码RNA的结构 - 动力学 - 功能关系。 我们的工具降低了发现选择性RNA配体的障碍。拟议的工作最终将打开 靶向RNA的新视野，化学和生物学科学家将轻松筛选出该地平线 针对广泛的RNA分子（包括与人类疾病相关的RNA分子）的小分子探针。这样的 功能将使RNA的治疗潜力得到充分利用，并固有地改变我们 了解分子生物学。