CAREER: Frameworks for RNA Recognition

职业：RNA 识别框架

• 批准号: 9876246
• 负责人: Richard Roberts
• 金额: $ 50万
• 依托单位: California Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-02-01 至 2004-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9876246&HistoricalAwards=false
• 关键词: CAREER; Frameworks; RNA; Recognition

Roberts9876246RNA-protein interactions are of central biological importance as they provide the means to connect genetic information to cellular biochemistry. Work over the last decade has elucidated a number of protein motifs that are capable of sequence and/or structure specific RNA recognition. However, it is neither possible to design a protein sequence that will bind a chosen RNA target nor predict which motif would be most appropriate for a given recognition problem. The investigator has therefore chosen to pursue an in vitro genetic strategy to isolate RNA binding proteins. The in vitro strategy will be pursued using RNA-protein fusions, protein molecules covalently attached to the mRNA which encodes them. The investigator proposes to explore and compare random sequence protein libraries to two protein motifs that have the potential to act as general frameworks for RNA recognition: 1) the arginine rich (ARM) motif, and 2) a structural analog of the RNP domain, the B1 domain of protein G. The selection experiments will provide a wealth of examples that will either support or challenge the current ability to predict protein structure. Biochemical and physical analysis of these examples should provide insight into which scaffolds are the most general. In addition, the information from the selection experiments will be fed back into the design process in an iterative fashion to improve the overall design of the frameworks and selections.The design of new proteins is one of the fundamental challenges facing biochemists. This is because it is not currently possible to design a protein with a set of rational steps analogous to the construction of a building. An alternative approach is to construct many different proteins (millions to trillions) and select the few that have desired functional properties. The immune system uses precisely this strategy for our defense, making billions of proteins based on a common framework--an antibody. The investigator proposes to examine new frameworks for their ability to recognize RNA molecules. Using newly developed techniques, the investigator's lab will examine trillions of sequences in an effort to develop general reagents to improve our understanding of protein function.

Roberts9876246 RNA与蛋白质的相互作用具有重要的生物学意义，因为它们提供了将遗传信息与细胞生物化学联系起来的手段。过去十年的工作已经阐明了许多能够识别序列和/或结构特异性RNA的蛋白质基序。然而，既不可能设计一个与选定的RNA目标结合的蛋白质序列，也不可能预测哪个基序最适合给定的识别问题。因此，研究人员选择了一种体外遗传策略来分离RNA结合蛋白。体外策略将使用RNA-蛋白质融合，蛋白质分子共价连接到编码它们的信使核糖核酸上。研究人员建议探索并比较随机序列蛋白质文库和两个有可能作为RNA识别一般框架的蛋白质基序：1)富含精氨酸(Arm)基序，以及2)RNP结构域的结构类似物，即蛋白质G的B1结构域。选择实验将提供大量的例子，这些例子要么支持要么挑战目前预测蛋白质结构的能力。通过对这些例子的生化和物理分析，应该能够洞察哪些支架是最普遍的。此外，筛选实验的信息将以迭代的方式反馈到设计过程中，以改进框架和选择的整体设计。设计新的蛋白质是生物化学家面临的根本挑战之一。这是因为目前还不可能设计出一种蛋白质，它具有一套类似于建筑建造的合理步骤。另一种方法是构建许多不同的蛋白质(数百万到数万亿)，并选择少数具有所需功能特性的蛋白质。免疫系统正是使用这种策略来防御，在一个共同的框架--抗体--的基础上制造数十亿种蛋白质。这位研究人员建议检查它们识别RNA分子的能力的新框架。使用新开发的技术，研究人员的实验室将检查数万亿条序列，努力开发通用试剂，以提高我们对蛋白质功能的理解。