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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

基本信息

批准号：
10667429
负责人：
Amanda E Hargrove
金额：
$ 42.5万
依托单位：
DUKE UNIVERSITY
依托单位国家：
美国
项目类别：
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

项目摘要

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靶向的兴趣激增，但治疗潜力目前受到缺乏RNA靶向的限制。基本了解如何实现选择性和功能性小分子靶向。总体我们研究计划的重点是阐明小分子选择性的关键驱动因素：RNA识别和应用这些原理来促进RNA靶向化学探针和治疗剂的开发，调节RNA功能。开始，我们确定了生物的物理化学，结构和空间特性，活性RNA配体不同于蛋白质靶向配体。RNA结合的合成阐述将支架引入到富含这些特性的文库中导致了对疾病相关RNA的识别的改善，包括病毒和长的非编码RNA结构。我们使用模式识别协议来识别RNA 拓扑结构，可以被小分子差异识别，并阐述了这种技术，可视化构象变化。这一综合工作取得了显著的成功，肠道病毒71 RNA，其中我们的配体诱导了一个戏剧性的构象变化，增加了结合的一个抑制人类蛋白质，减少病毒翻译，并抑制病毒复制。我们的方法也是显示出针对SARS-CoV 2调节RNA的初步成功。在这些成就的基础上，我们建议开发新的文库和筛选方法，以了解对一系列更复杂的三级和四级结构的功能选择性。洞察最关键驱动因素将通过模式识别/机器学习分析以及一种基于整体的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细胞的高通量测定中显示。这些发现将得到进一步加强，阐明致癌长非编码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。这项拟议中的工作将最终打开一个 RNA靶向的新视野，其中化学和生物科学家将容易和富有成效地筛选小分子探针针对广泛的RNA分子，包括与人类疾病相关的RNA分子。等这些能力将使RNA的治疗潜力得到充分利用，并从根本上改变我们的了解分子生物学。

项目成果

期刊论文数量（17）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Multiassay Profiling of a Focused Small Molecule Library Reveals Predictive Bidirectional Modulation of the lncRNA MALAT1 Triplex Stability In Vitro.

DOI：
10.1021/acschembio.2c00124
发表时间：
2022-09-16
期刊：
ACS chemical biology
影响因子：
4
作者：
Zafferani M;Martyr JG;Muralidharan D;Montalvan NI;Cai Z;Hargrove AE
通讯作者：
Hargrove AE

RT-qPCR as a screening platform for mutational and small molecule impacts on structural stability of RNA tertiary structures.

RT-QPCR作为突变和小分子的筛选平台对RNA三级结构的结构稳定性影响。

DOI：
10.1039/d2cb00015f
发表时间：
2022-07-06
期刊：
RSC CHEMICAL BIOLOGY
影响因子：
4.1
作者：
Zafferani, Martina;Muralidharan, Dhanasheel;Montalvan, Nadeska, I;Hargrove, Amanda E.
通讯作者：
Hargrove, Amanda E.

Differentiation and classification of RNA motifs using small molecule-based pattern recognition.

使用基于小分子的模式识别对 RNA 基序进行区分和分类。