Toward Atomic-Accuracy Design of Functional RNAs

 描述(由申请人提供)：一种新的范例已经出现，它利用基于RNA的分子机器作为传感器来调节新的基因网络，并作为治疗方法来治疗艾滋病毒和乳腺癌等疾病。这些生物分子机器利用RNA的非凡能力，采用复杂的3D形状，执行催化，并改变形状，以响应细胞和病毒分子。此外，RNA可以用已有的合成方法大量生产，并可以与越来越方便的细胞递送方法相结合。不幸的是，尽管RNA作为设计媒介的潜力很大，但RNA折叠和设计的不准确模型严重阻碍了基于RNA的疗法和传感器的发展，这需要耗时的选择方法和反复试验的精炼。为了加速基于RNA的技术的产生，我开发了RNAMake，这是第一个自动化的RNA3D设计工具包。RNAMake利用RNA基序，这是RNA3D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目前实现基于RNA的疗法设计自动化的障碍：首先，通过在3D设计问题中测试所有已知基序的模块化，从而彻底表征它们的模块化特性，以生成高度模块化构建块的精选数据库，增加人们对RNAMake设计的信心；其次，展示RNAMake开发一种新型基于RNA的传感器的直接方法，以检测属于肥厚型心肌病(HCM)关键指标的mir129、mir212、mir21和mir208a miRNAs。在这两个目标中，我将结合使用大规模平行形状化学测绘、选择性结晶学(Jeffrey Kieft)、FRET测量(William Greenlive)和基于细胞培养的分析(Euan Ashley)来评估成功。这项提议是高度协作的，将包括结构生物学、遗传学和医学在内的各种领域的实验聚集在一起。成功完成设定的目标，将产生公开可访问的数据库中模体模块化的第一个详细特征，第一个可供任何RNA工程小组使用的3D设计自动化平台，以及其用于生物医学相关RNA机器的高调图解。此外，这项工作将作为我教职生涯的重点继续下去。

 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.