Toward Atomic-Accuracy Design of Functional RNAs

 描述（由申请人提供）：已经出现了一种新的范例，利用基于RNA的分子机器作为传感器来调节新的基因网络，并作为治疗剂来治疗诸如HIV和乳腺癌的疾病。这些生物分子机器利用RNA的非凡能力，采用复杂的3D形状，进行催化，并响应细胞和病毒分子改变形状。此外，RNA可以使用已建立的合成方法大量生产，并且可以与越来越容易的细胞递送方法相结合。不幸的是，尽管RNA具有作为设计介质的潜力，但基于RNA的治疗剂和传感器的开发受到RNA折叠和设计的不准确模型的严重阻碍，需要耗时的选择方法和试错法改进。为了加速基于RNA的技术的产生，我开发了RNAMake，这是第一个自动化RNA 3D设计工具包。RNAMake利用RNA基序，RNA 3D结构的构建块，在少数情况下，已被证明是模块化的。我建议通过以下目标来解决当前的障碍，以自动设计基于RNA的治疗方法：首先，通过在3D设计问题中测试所有已知基序的模块性，以生成高度模块化构建块的策划数据库，从而全面表征所有已知基序的模块性，增加RNAMake设计的信心，其次，展示RNAMake开发新型基于RNA的传感器以检测mir129的直接方法，mir212、mir21和mir208a miRNAs是肥厚型心肌病（HCM）的关键指标。在这两个目标中，我将通过使用大规模并行的SHAPE化学作图，选择性晶体学（Jeffrey Kieft），FRET测量（William Greenleaf）和基于细胞培养的测定（Euan阿什利）的组合来评估成功。该提案是高度合作的，汇集了包括结构生物学，遗传学和医学在内的各种领域的实验。成功完成所提出的目标，将产生第一个详细的特征基序模块化在一个可访问的数据库，第一个自动化平台的3D设计，可用于任何RNA工程组，和高调的插图，其使用生物医学相关的RNA为基础的机器。此外，这项工作将继续作为我的教师职业生涯的焦点。

 DESCRIPTION (provided by applicant): A new paradigm has emerged to utilize RNA-based molecular machines as sensors to regulate new gene networks and as therapeutics to treat diseases such as HIV and breast cancer. These biomolecular machines harness RNA's extraordinary ability to adopt complex 3D shapes, perform catalysis, and change shapes in response to cellular and viral molecules. Furthermore, RNA can be produced in large quantities using established synthesis and can be coupled to increasingly facile cellular delivery methods. Unfortunately, despite RNA's potential as a design medium, development of RNA-based therapeutics and sensors are significantly hindered by inaccurate models of RNA folding and design, necessitating time-consuming selection methods and trial-and-error refinement. To accelerate the generation of RNA-based technology, I have developed RNAMake, the first automated RNA 3D design toolkit. RNAMake utilizes RNA motifs, the building blocks of RNA 3D structure which, in a few cases, have been shown to be modular. I propose to resolve current barriers to automate the design of RNA-based therapeutics through the following aims: First exhaustively characterizing the modularity of all known motifs by testing them in 3D design problems to generate a curated database of highly modular building blocks, increasing the confidence in RNAMake's designs and second to demonstrate RNAMake's straightforward approach to developing a novel RNA-based sensors to detect mir129, mir212, mir21, and mir208a miRNAs which are critical indicators of hypertrophic cardiomyopathy (HCM). In both of these aims, I will evaluate success through using a combination of massively parallel SHAPE chemical mapping, selective crystallography (Jeffrey Kieft), FRET measurements (William Greenleaf) and cell culture based assays (Euan Ashley). This proposal is highly collaborative, bringing together experiments a wide variety of fields including Structural Biology, Genetics and Medicine. Successful completion of the aims set forth, will yield the first detailed characterizatin of motif modularity in a publically accessible database, the first automated platform for 3D design that can be used by any RNA engineering group, and high-profile illustrations of its use for biomedically relevant RNA-based machines. In addition this work will be pursued subsequently as the focal point of my faculty career.