SHAPE RNA Bioinformatics for Therapeutics and Translational Research

 描述（由申请人提供）：只有2%的人类基因组被翻译成蛋白质，而大约70%被转录成RNA。这些RNA中复杂的高阶结构从根本上影响着关键的生物过程。例如，核糖体中的RNA结构是许多抗生素的靶标，RNA病毒（如HIV和流感）基因组中的结构对于病毒复制和发病机理至关重要，与人类疾病最密切相关的单核苷酸多态性中约有一半发生在非编码区，可能反映了异常的RNA结构。这些结构应该在小分子药物发现工作中加以利用。Weeks实验室开发了一种化学探测策略，称为SHAPE-MaP，可以准确地报告生理相关背景下的RNA结构。尽管独立的研究小组将SHAPE描述为RNA结构分析的“黄金标准”，但以目前的形式，SHAPE-MaP代表了一种尖端但研究级的技术。该技术基于强大的化学和“数字”大规模并行测序数据，原则上可以完全自动化。因此，Ribomeirs的长期愿景是使SHAPE-MaP成为一种平台技术，应用于药物发现，转化研究和基础生物学发现。在这项工作中，我们将通过两个目标进行概念验证研究，以解决非专家实验室采用的关键生物信息学和计算障碍：（1）创建高效的商业级软件，用于将大规模并行测序数据自动解卷积为定量的、经验证的SHAPE-MaP反应性谱，以及（2）自动化分析管道以允许RNA结构的快速建模，候选功能基序的发现，以及配体和候选药物结合的定量。第二阶段的进展将通过可行性数据来证明，这些数据表明，新手研究生或技术人员级别的用户能够使用自动化、容错软件分析和诊断RNA结构探测实验，并识别具有可能功能重要性的RNA特征。在第二阶段，RibomeLab将全面完善和集成自动化计算分析，并托管在共享的云计算平台上，并将为制药和学术客户以及合作者开发高效的咨询服务。SHAPE技术的广泛应用将改变基于RNA的新型疗法的设计、RNA靶点的发现以及小分子-RNA相互作用的分析和验证。

 DESCRIPTION (provided by applicant): Only 2% of the human genome is translated into proteins, whereas roughly 70% is transcribed into RNA. Complex higher-order structures in these RNAs fundamentally affect critical biological processes. As examples, RNA structures in the ribosome are the targets of many antibiotics, structures in the genomes of RNA viruses like HIV and influenza are essential for viral replication and pathogenesis, and roughly half of the single nucleotide polymorphisms that are most strongly associated with human diseases occur in non-coding regions and likely reflect abnormal RNA structures. These structures should be exploited in small-molecule drug discovery efforts. The Weeks laboratory has developed a chemical probing strategy, called SHAPE-MaP that accurately reports on RNA structure in physiologically relevant contexts. Although independent groups describe SHAPE as the "gold standard" of RNA structure analysis, in its current form, SHAPE-MaP represents a cutting-edge but research- grade technology. This technology is based on robust chemistry and "digital" massively parallel sequencing data and, in principle, could be fully automated. The long-term vision of Ribometrix is thus to make SHAPE-MaP a platform technology with applications in drug discovery, translational research, and basic biological discovery. In this work, we will conduct proof-of-concept studies to solve critical bioinformatic and computational impediments to adoption by non-expert laboratories via two Aims: (1) Create efficient commercial-grade software for automated deconvolution of massively parallel sequencing data into quantitative, validated SHAPE-MaP reactivity profiles and (2) Automate analysis pipelines to allow rapid modeling of RNA structures, discovery of candidate functional motifs, and quantification of ligand and drug candidate binding. Progress to Phase 2 will be justified by feasibility data showing that novice graduate student or technician-level users are able to analyze and diagnose RNA structure probing experiments and identify RNA features with likely functional importance using automated, error-tolerant software. In Phase 2, Ribometrix will fully refine and integrate automated computational analysis to be hosted on a shared cloud computing platform and will develop efficient consulting services for pharmaceutical and academic customers and collaborators. Widespread access to SHAPE technology will transform design of novel RNA-based therapeutics, discovery of RNA targets, and analysis and validation of small molecule-RNA interactions.