Computational Methods for Tertiary RNA Folding and Novel RNA Design

项目摘要（NSF 0727001）三级RNA折叠和新型RNA设计的计算方法最近的发现揭示了RNA形成复杂三维结构的奇妙能力，以及除存储生物信息外的许多分子功能。RNA新发现的力量正被用于生物工程和纳米技术，用于设计和应用检测化合物（例如毒素）的生物传感器，用于实现更快化学反应的RNA酶，用于控制细胞中蛋白质合成的RNA开关，以及用于监测基因表达的RNA微阵列。RNA科学的这些进步主要依赖于实验技术（例如，x射线晶体学）。然而，对于RNA来说，系统的理论三维结构确定和设计方法在很大程度上是缺乏的，这些方法极大地促进了蛋白质科学的发展。这一空白阻碍了在生物工程和纳米技术中推进新兴RNA应用所需的实验和理论工具的整合。本研究的重点是开发RNA三维结构预测和设计的计算技术。对于RNA 3D结构预测，研究人员研究了算法开发问题，包括计算和测试RNA统计电位，以及开发/应用有效的蒙特卡罗构象采样算法，结合片段组装方法，这是一种成功的蛋白质结构预测方法。特别是，研究人员研究了多体相互作用在RNA 3D结构预测中的作用。对于RNA 3D设计，研究人员专注于通过系统计算方法设计具有定制功能的新型RNA的程序。这项工作包括将RNA 2D/3D折叠算法与先进的动力学分析工具（例如，QM/MM，过渡路径采样）相结合，以筛选和阐明所设计RNA的结构，动力学和配体结合特性。从研究中得出的用于RNA 3D结构预测和设计的计算工具正在作为软件包提供给研究界。

Project Abstract (NSF 0727001)Computational Methods for Tertiary RNA Folding and Novel RNA DesignRecent discoveries have revealed RNA's wonderful capacity to form complex three-dimensional structures, as well as perform many molecular functions beyond storage of biological information. RNA's newly realized powers are being exploited in bioengineering and nanotechnology for design and application of biological sensors for detecting chemical compounds (for example, toxins), RNA enzymes for enabling faster chemical reactions, RNA switches for controlling protein synthesis in the cell, and RNA microarrays for monitoring gene expression. These advances in RNA science have relied mostly on experimental techniques (for example, X-ray crystallography). However, the systematic theoretical 3D structure determination and design approaches that have greatly benefited protein science are largely lacking for RNA. This void hampers the integration of experimental and theoretical tools required for advancing emerging RNA applications in bioengineering and nanotechnology. This research focuses on developing computational technologies for RNA 3D structure prediction and design. For RNA 3D structure prediction, the investigators study algorithmic development issues involving calculating and testing RNA statistical potentials, and developing/applying effective Monte Carlo conformational sampling algorithms coupled with the fragment assembly approach, a successful method for protein structure prediction. In particular, the investigators examine the role of multibody interactions in RNA 3D structure prediction. For RNA 3D design, the investigators focus on procedures for designing novel RNAs with tailored functions by a systematic computational approach. This work involves integrating RNA 2D/3D folding algorithms with advanced dynamics analysis tools (for example, QM/MM, transition path sampling) to screen and elucidate the structural, dynamical, and ligand-binding properties of designed RNAs. The computational tools for RNA 3D structure prediction and design resulting from the studies are being made available as a software package to the research community.