RATIONAL DESIGN TOOLS FOR ANTISENSE NUCLEIC ACIDS

描述（由申请人提供）：本项目的长期目标是开发新的算法和方法，用于改进RNA高级结构的预测，以及合理有效地设计反义核酸。反义寡核苷酸、反式切割核酶和短干扰RNA已成为实现有效基因下调的越来越重要的RNA靶向工具。它们对于人类、模式生物和感染性病原体中基因和基因产物的高通量功能研究以及针对人类疾病的新治疗靶标和药剂的鉴定和验证至关重要。为了有效，这些反义核酸分子需要良好的靶可及性，这主要由靶RNA的二级结构决定。mRNA和病毒RNA的二级结构通常是未知的，并且难以通过实验手段阐明。因此，计算方法可能是有价值的RNA结构的测定。然而，传统的RNA折叠算法没有充分解决预测中的不确定性问题或长链RNA的潜在替代结构问题。最近，一种新的统计抽样方法预测RNA二级结构提出了一个令人满意的解决方案，这些长期存在的问题。与传统方法相比，这种新方法已被证明为预测信使RNA结构和有效的反义靶点提供了重要的改进。本申请的目的是开发用于反式切割核酶的合理和有效设计的算法和方法。这将通过利用统计抽样方法进行目标可及性预测和核酶设计（目标1），通过实验测试计算设计的核酶在体外和体内，并通过统计分析和建模的实验数据（目标2），以进一步改善设计方法来实现。最后，将开发一个包含核酶设计工具的软件模块，并通过网络服务器提供给科学界（目标3）。该项目有望为RNA高级结构预测提供改进的算法，为反义核酸工程提供更有效的方法。在后基因组时代，软件和Web服务器的可用性将大大促进反义核酸在高通量功能基因组学中的应用。

DESCRIPTION (provided by applicant): The long term goal of this project is to develop novel algorithms and methods for improved prediction of RNA higher order structures, and for the rational and efficient design of antisense nucleic acids. Antisense oligonucleotides, trans-cleaving ribozymes and short interfering RNAs have emerged as increasingly important RNA-targeting tools for achieving efficient gene down-regulation. They are essential for high throughput functional studies of genes and gene products in humans, model organisms and infectious pathogens, as well as for the identification and validation of new therapeutic targets and agents against human diseases. To be effective, these antisense nucleic acid molecules require good target accessibility, which is primarily determined by the secondary structure of the target RNA. The secondary structures of mRNAs and viral RNAs are generally unknown, and are difficult to elucidate by experimental means. Therefore, computational methods could be valuable for the RNA structural determination. However, conventional RNA folding algorithms have not adequately addressed either the issue of uncertainty in the prediction or the issue of potential alternative structures for long-chain RNAs. Recently, a novel statistical sampling approach to RNA secondary structure prediction has presented a satisfying solution to these longstanding problems. This new method has been shown to offer important improvements for the prediction of messenger RNA structures and effective antisense targets, when compared to conventional methods. The objective of the present application is to develop algorithms and a methodology for the rational and efficient design of trans-cleaving ribozymes. This will be achieved by taking advantage of the statistical sampling method for target accessibility prediction and ribozyme design (Aim 1), by experimentally testing the computationally designed ribozymes both in vitro and in vivo, and to further improve the design methodology through statistical analysis and modeling of the experimental data (Aim 2). Finally, a software module incorporating the ribozyme design tools will be developed and made available to the scientific community through a Web server (Aim 3). Improved algorithms for RNA higher order structure prediction and more effective methods for the engineering of antisense nucleic acids are expected to result from this project. In the post-genomic era, the availability of the software and the Web server will substantially facilitate applications of antisense nucleic acids in high throughput functional genomics.