Computational Approaches for RNA StructureFunction Determination

RNA 结构功能测定的计算方法

基本信息

批准号：
7732920
负责人：
BRUCE A. SHAPIRO
金额：
$ 34.19万
依托单位：
DIVISION OF BASIC SCIENCES - NCI
依托单位国家：
美国
项目类别：
财政年份：
资助国家：
美国
起止时间：
至
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/7732920
关键词：
3-Dimensional Algorithms Amino Acid Motifs Aplastic Anemia Base Pairing Binding Sites Biological Biological Assay Biology Carrier Proteins Catalysis Categories Cell Proliferation Cells Characteristics Computer software Computing Methodologies Consensus Coupled Data Analyses Databases Dengue Development Dyskeratosis Congenita Elements Environment Escherichia coli Evolution Flavivirus Functional RNA Gene Expression Gene Silencing Genes Genetic Programming Genome HIV Helix (Snails)Hepatitis Delta Virus Hereditary Disease Higher Order Chromatin Structure Imagery Indium Intercistronic Region Internet Java Knowledge Laboratories Linux Machine Learning Malignant - descriptor Malignant Neoplasms Membrane Methodology Methods Modeling Molecular Molecular Conformation Object Attachment Ontology Ornithine Decarboxylase Pathway interactions Pattern Plant Viruses Population Process RNA RNA Folding RNA Sequences RNA analysis Radar Research Ribosomal RNA Rotavirus Running Sequence Alignment Series Site Structural Models Structure Structure-Activity Relationship System Telomerase Thermodynamics Transcriptional Activation Transcriptional Regulation Transfer RNA Translating Translation Initiation Translations Turnip - dietary United States National Institutes of Health Untranslated Regions Up-Regulation Update Viral Virus Work base computerized tools concept data mining drug development ear helix human SLPI protein improved innovation insight molecular dynamics molecular modeling programs stem three dimensional structure three-dimensional modeling tool user-friendly web-accessible

项目摘要

;RNA Secondary Structure Prediction and Analysis Software: We continue to improve upon an RNA folding algorithm (MPGAfold) that uses concepts from genetic algorithms and apply this algorithm to various biological problems (see below). An optimized version that was adapted to run on LINUX clusters, using MPI is available upon request. The algorithm is capable of predicting RNA pseudoknots and exploring folding pathways that contain multiple functional conformations. A Java-based visualizer for depicting population evolution has also been developed which when coupled with the MPI version of MPGAfold makes the system more user friendly and portable and allows for a detailed exploration of the structure population space. STRUCTURELAB, the heterogeneous bioinformatical RNA analysis workbench, which permits the use of a broad array of approaches for RNA structure analysis, has been continually enhanced. It has been used for the visualization of folding pathways in conjunction with the genetic algorithm and with dynamic programming algorithms (e.g. mFOLD). STRUCTURELAB and other new tools contain several features which when used together, act as set of data mining methodologies to aid in the discovery of RNA folding patterns. These systems have been adapted to other environments inside and outside our laboratory and NIH and are available for download from our newly enhanced Web site. KNetFold our new algorithm for RNA secondary structure prediction has also been enhanced. The methodology integrates thermodynamic and compensatory base change information using an innovative machine-learning algorithm (a hierarchical network of k-nearest neighbor classifiers). KNetFold has been shown to outperform other RNA secondary structure prediction programs. Another program CorreLogo has also been enhanced. It depicts in a 3-dimensional plot correlations that exist between base pairs in a secondary structures. These methodologies use mutual information derived from a sequence alignment. Both KnetFold and CorreLogo can be found as Web servers on our website. They are also downloadable from our newly configured web site. We developed a new Web server called RADAR that provides a multitude of functionality for RNA data analysis. It can align structure-annotated RNA sequences so that both sequence and structure information are used during the alignment process. This server can perform pairwise structure alignment, multiple structure alignment, database search and clustering. RADAR provides two major features. It can perform constrained alignment of RNA secondary structures, and the prediction of the consensus structure for a set of RNA sequences. In addition, a new RNA secondary structure Web accessible database, RmotifDB was developed. RmotifDB is also integrated with a gene ontology database. Algorithms have been developed to determine regions within genomes that are indicative of non-coding RNAs. Structural characteristics which distinguish those regions that may occur in intergenic or control regions of RNA are being determined. These methods have been applied in various biological contexts. Determination of Biologically Related RNA Secondary Structure Folding Characteristics: The above described computational tools have been employed in studying RNA structural characteristics, folding pathways and functional intermediates of various RNAs. These are exemplified by the analysis of the folding pathways of the HIV 5' and 3' non-coding regions; the control mechanisms of the hepatitis delta virus, interlukin-2, rotavirus, dengue fever (and the flaviviruses in general) and the turnip crinkle virus. They are also providing insight into cancer development that is inducible by the up regulation of eIF4E or controlled by the presence or absence of PDCD4. Algorithms that were developed for the determination of non-coding RNAs in genomes are being applied to the intergenic regions of E. coli, Musashi binding sites and to determine potential structural RNA elements that are involved in RNA translation initiation. Each of these sites is proving to contain unique features and characteristics that are inherent to the different biological domains being examined. Software for RNA 3D Structure Prediction: We developed a program, RNA2D3D, for interactively exploring RNA 3D conformations at the all atom level. It works on the premise of generating three-dimensional models of a RNA from a given RNA secondary structure. The secondary structure may be generated by any one of several methodologies. The program generates structures very rapidly, allowing the import, for example, of a secondary structure description of a 1542 base 16S rRNA and generating a rough 3D model in less than a second. As part of the input secondary structure representation, the specification of pseudoknot interactions is also permitted. RNA2D3D also allows for the specification of coaxial stacking between stems and compactification, which essentially extends an A-form helix into loops that can form non-canonical base pairs. This latter feature is quite helpful because often loops are not found as single strands. General molecular editing features such as rotating or translating conformational segments are also permitted. RNA motifs from the Protein Databank (PDB) can also be imported and attached to the modeled structure. The Tinker molecular dynamics software can be invoked permitting the refinement of bond angles and distances. Three-Dimensional RNA Structural Modeling and Analysis: We have predicted the structure of the wild-type telomerase pseudoknot and have done molecular dynamics studies on the RNA hairpin and pseudoknot that are important structural elements in telomerase. These studies show that an unusual sequence of non-canonical base pairs have dynamic conformational characteristics that induce the formation of the pseudoknot. These results have significant implications concerning genetic diseases such as dyskeratosis congenita, aplastic anemia and cancer. New Paradigm for Translational Enhancement Discovered: We applied our secondary structure prediction methodologies, 3-D modeling methodologies, including the molecular modeling software RNA2D3D, and molecular dynamics to discover a unique motif in the turnip crinkle virus 3' UTR. It is becoming evident that the 3' UTRs of cellular and viral mRNAs harbor elements that function in gene expression by enhancing translation using as yet unknown mechanisms. Some of these cellular mRNAs, including ornithine decarboxylase, encode products whose overproduction leads to cell proliferation. To determine the function of these elements, we employed a simple model virus, Turnip crinkle virus (TCV). TCV, like many plant viruses, is translated in a cap-independent fashion and contains a 3' proximal region that together with the 5' UTR synergistically enhances translation. We have gained a significant understanding of the function of this 3' element. We used MPGAfold to identify a series of hairpins and one pseudoknot that have been confirmed genetically. Using this RNA secondary structural information in conjunction with RNA2D3D for RNA 3D molecular modeling we predicted that a series of three hairpins and two pseudoknots structurally resembled a tRNA. This has been experimentally verifi [summary truncated at 7800 characters]

; RNA二级结构预测和分析软件：我们将继续改进RNA折叠算法（MPGAFOLD），该算法使用遗传算法的概念，并将此算法应用于各种生物学问题（见下文）。可以根据要求使用MPI的优化版本，该版本适用于Linux群集上。该算法能够预测RNA伪单元并探索包含多种功能构象的折叠途径。还开发了一种基于Java的可视化器来描述人口演变，当与MPI版本的MPGafold结合使用时，该系统使系统更加用户友好和便携，并允许对结构人口空间进行详细的探索。构造的异质生物信息RNA分析工作台允许使用广泛的方法进行RNA结构分析，但已不断增强。它已用于与遗传算法和动态编程算法（例如Mfold）结合使用折叠途径。结构图和其他新工具包含多个功能，当一起使用时，充当一组数据挖掘方法，以帮助发现RNA折叠模式。这些系统已适用于我们实验室和NIH外部和外部的其他环境，可从我们新增强的网站下载。我们用于RNA二级结构预测的新算法也得到了增强。该方法使用创新的机器学习算法（K-Nearest邻居分类器的层次网络）整合了热力学和补偿基础变化信息。 Swinfold已显示出优于其他RNA二级结构预测程序。另一个程序相关程序也得到了增强。它描绘了二次结构中基本对之间存在的三维图相关性。这些方法使用序列比对得出的共同信息。 Knetfold和Correlogo都可以在我们的网站上找到网络服务器。它们也可以从我们新配置的网站下载。我们开发了一个名为Radar的新Web服务器，该服务器为RNA数据分析提供了多种功能。它可以对齐结构注销的RNA序列，以便在对齐过程中使用序列和结构信息。该服务器可以执行成对结构对齐，多结构对齐，数据库搜索和聚类。雷达提供了两个主要功能。它可以执行RNA二级结构的约束比对，以及一组RNA序列的共有结构的预测。此外，开发了一个新的RNA二级结构Web可访问数据库RMOTIFDB。 RMOTIFDB也与基因本体数据库集成在一起。已经开发出算法来确定指示非编码RNA的基因组中的区域。正在确定区分可能发生在RNA间或对照区域的区域的结构特征。这些方法已应用于各种生物学环境。确定生物学相关的RNA二级结构折叠特性：上述计算工具已用于研究RNA结构特征，折叠途径和各种RNA的功能中间体。这些通过分析HIV 5'和3'非编码区域的折叠途径来举例说明；肝炎病毒，Interlukin-2，轮状病毒，登革热（以及一般的黄病毒）和萝卜皱纹病毒的控制机制。他们还提供了对癌症发展的见解，该癌症的发展可通过EIF4E的加强调节或受PDCD4的存在或不存在控制。开发用于确定基因组中非编码RNA的算法已应用于大肠杆菌，肌肉结合位点的基因间区域，并确定参与RNA转换启动的潜在结构RNA元件。这些站点中的每一个都包含所检查的不同生物领域固有的独特特征和特征。 RNA 3D结构预测的软件：我们开发了一个程序RNA2D3D，用于在全原子级别进行交互式探索RNA 3D构象。它在给定RNA二级结构中生成RNA的三维模型的前提。二级结构可以由几种方法中的任何一种生成。该程序非常迅速地生成结构，允许导入例如1542碱基16S rRNA的二级结构描述，并在不到一秒钟的时间内生成粗糙的3D模型。作为输入二级结构表示的一部分，还允许伪诺相互作用的规范。 RNA2D3D还允许在茎和紧凑型之间进行同轴堆叠的规定，这基本上将A形螺旋延伸到可以形成非典型基础基对的环中。后一个功能非常有用，因为通常不会发现循环作为单链。还允许通用分子编辑特征，例如旋转或翻译构象段。来自蛋白质数据库（PDB）的RNA基序也可以进口并附加到建模结构上。可以调用Tinker Molecular Dynamics软件，允许键角和距离的完善。三维RNA结构建模和分析：我们已经预测了野生型端粒酶假诺的结构，并就RNA发夹和伪not进行了分子动力学研究，这是端粒酶中重要的结构元素。这些研究表明，非规范基碱对的异常序列具有诱导伪诺形成的动态构象特征。这些结果对遗传疾病（例如脑膜炎，性障碍性贫血和癌症）具有重要意义。发现了转化增强的新范式：我们应用了二级结构预测方法，3-D建模方法，包括分子建模软件RNA2D3D和Molecular Dynamics，以发现萝卜Crinke Crinke Virus 3'Utr中的独特基序。越来越明显的是，通过使用AS尚未知道的机制增强翻译，细胞和病毒mRNA的3'UTR在基因表达中起作用。这些细胞mRNA中的一些，包括鸟嘌呤脱羧酶，编码其过量生产导致细胞增殖的产物。为了确定这些元素的功能，我们采用了简单的模型病毒，萝卜皱纹病毒（TCV）。与许多植物病毒一样，TCV以帽含量独立的方式翻译，并包含一个3'近端区域，并与5'UTR协同增强翻译相同。我们已经对该3'元素的功能有了重大的了解。我们使用mpgafold来识别一系列的发夹和一个伪造的发夹，这些发夹已在遗传上得到证实。使用此RNA二级结构信息与RNA2D3D用于RNA 3D分子建模，我们预测，一系列三个发夹和两种伪not在结构上类似于tRNA。这是通过实验性验证[以7800个字符截断的摘要]