Identification, Discovery, and Public Archiving of RNA Structural Motifs

项目摘要 摘要非编码RNA(NcRNAs)在催化、基因等生物过程中发挥着重要的功能。 表达调控和RNA剪接。NcRNA所扮演的各种角色由它们的特性决定。 立体三维结构。RNA结构基序是ncRNAs中反复出现的结构成分。核糖核酸的结构 基序具有保守的结构，因此，预计具有类似的生物学或结构功能。 例如，扭结-转折基序在不同种类的ncRNA中都存在，其中大多数与蛋白质有关 具有约束力的活动。基序结构的任何变化都有可能导致RNA功能的丧失 结构主题，在某些情况下可能导致严重的疾病。因此，对RNA结构基序的研究将 帮助我们阐明许多疾病的机制，并导致新的治疗策略的发展。 在生物医学研究需求的推动下，人们提出了许多计算方法来检测 寻找已知主题的实例或发现新奇的家族。最近，快速增长的可分辨RNA的数量 3D Structures促使开发新的工具来利用PDB中的海量资源。在我们的 意见认为，大规模数据集将支持两种新的RNA结构基序分析方法：生成 ProfiLES用于表示模体家族和搜索新实例，并识别结构和功能 不同主题之间的关系。在这个提案中，我们的目标是设计一套基于 关于这两个想法。首先，我们将构建3D位置特定fic评分矩阵(PSSM)作为专业fiLES来表示 已发现的核糖核酸结构基序家族中的碱基配对相互作用和发展基于PRO-fi的核糖核酸 结构主题搜索工具。考虑到现有的所有RNA结构基序搜索程序 依靠共识，PROfiLES的推出将创造一个极大的机会来提高搜索的准确性。在……里面 同时，新的PROfiLE模型将为我们提供一种描述基序家族的形式化方法，这是非常有意义的 对于理解RNA3D结构与其功能之间的关系至关重要。第二，我们 将区分Motif家族成员的结构特征，以识别亚家族，并研究其潜在的再 家庭之间的关系，以识别氏族和模块。来自不同家族的RNA结构基序可以 共享相似的结构特征，并且它们还可以相互作用以执行特定的fic功能。 据我们所知，目前还没有关于RNA结构基序之间的关系的研究。 现在，从聚类结果中新发现的RNA基序家族为我们提供了一个坚实的基础 在家庭内部和家庭间两个层面进行进一步研究。在实现这两个目标的同时，我们还提出 建立一个新的RNA结构基序数据库，将所有新发现的知识纳入这个项目。 这些工具还将作为用户友好的网络服务器实施，并与数据库集成，以提供 全方位的服务。我们期望拟议的工作将导致对RNA结构的更好的理解 Motives和Signifi可以促进生物医学研究。

Project Summary The non-coding RNAs (ncRNAs) play many functional roles in biological processes, such as catalysis, gene expression regulation, and RNA splicing. The various roles played by ncRNAs are determined by their charac- teristic 3D structures. RNA structural motifs are recurrent structural components in ncRNAs. The RNA structural motifs have conserved structures, and therefore, are expected to have similar biological or structural functions. For instance, the kink-turn motif is found in different kinds of ncRNAs and most of them are responsible for protein binding activities. Any alteration of the motif structures has the potential to result in loss-of-function of the RNA structural motif, and in some cases may cause severe diseases. Therefore, the study of RNA structural motif will help us to elucidate the mechanisms of many diseases and lead to the development of novel treatment strategies. Driven by the requirement of biomedical research, many computational methods have been proposed to detect instances of known motifs or to discover novel families. Recently, the rapidly increasing number of resolved RNA 3D structures urges the development of new tools to make use of the huge amount of resources in PDB. In our opinion, the large-scale dataset will support two new approaches for RNA structural motif analysis: generating profiles to represent motif families and to search for new instances, and identifying the structural and functional relationship among different motifs. In this proposal, we aim at devising a suite of computational methods based on these two ideas. First, we will build 3D position-specific scoring matrixes (PSSMs) as profiles to represent the base-pairing interactions in the discovered RNA structural motif families and develop profiled-based RNA structural motif search tools. Considering the fact that all the existing RNA structural motif searching programs rely on consensus, the introduction of profiles will create a great opportunity to improve the search accuracy. In the mean time, the new profile model will provide us a formal method to describe motif families, which is very critical for the understanding of the relationship between RNA 3D structures and their functionalities. Second, we will distinguish the structural features of motif family members to identify subfamilies, and study the potential re- lationship among families to recognize clans and modules. The RNA structural motifs from different families may share similar structural features, and they can also interact with each other to perform certain specific functions. As far as we know, there is no existing research about the mentioned relationships among RNA structural motifs. Now, the de novo discovery of RNA motif families from the clustering results grants us a solid foundation for further research at both intra- and inter-family levels. With the achievement of these two goals, we also propose to build a new RNA structural motif database to incorporate all the newly discovered knowledge in this project. The tools will also be implemented as user-friendly web servers and integrated with the database to provide a well-rounded service. We expect that the proposed work will lead to better understanding of the RNA structural motifs, and significantly promote biomedical research.