Automated Comparative Sequence Analysis of RNA Secondary and Tertiary Structure

RNA 二级和三级结构的自动比较序列分析

• 批准号: 10374883
• 负责人: DAVID H. MATHEWS
• 金额: $ 30.8万
• 依托单位: UNIVERSITY OF ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-01 至 2023-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10374883
• 关键词: Achievement; Adopted; Algorithmic Software; Algorithms; Base Pairing; Belief; Biology; Cells; Code; Computer software; Computing Methodologies; Conserved Sequence; Disease; Drug Targeting; Evolution; Explosion; Family; Genome; Goals; Health; Homology Modeling; Hour; Human; Length; Manuals; Methods; Modeling; Nucleotides; Output; Pharmaceutical Preparations; Pharmacologic Substance; Phylogenetic Analysis; Phylogeny; Problem Solving; Protocols documentation; Publishing; RNA; RNA Sequence Analysis; RNA Sequences; Reaction; Resolution; Ribosomal RNA; Role; Sequence Alignment; Sequence Homologs; Software Tools; Structure; Trees; Untranslated RNA; comparative; improved; information model; innovation; interest; knowledge base; rapid technique; restraint; three dimensional structure; three-dimensional modeling; tool; web server

Project Summary: RNA serves important roles as an information carrier and effector molecule. For many roles, a functional RNA must adopt a specific secondary or tertiary structure. Across evolution, these structures are more conserved than the sequence. By comparing multiple homologous sequences, structures can be inferred. We developed TurboFold as an accurate and rapid method for automating sequence comparison to predict conserved RNA secondary structures and alignments. We also expanded this with a knowledge-based potential to predict conserved non-canonical base pairs, which are the basis of tertiary structures. Expanding on our TurboFold method, we will develop new high-impact algorithms and software to solve important problems in RNA biology. First, we will develop new tools to estimate phylogenies for RNA and to use the phylogenetic relationships between sequences to more accurately predict structures and alignments. Second, we will improve tertiary structure modeling by using our predictions of conserved non-canonical pairs as restraints for building all-atom models. Third, we will develop new tools for homology modeling of secondary and tertiary structure, where a template structure for an RNA sequence from the same family exists.

项目概要： RNA作为信息载体和效应分子发挥着重要作用。对于许多角色， 有功能的RNA必须具有特定的二级或三级结构。在进化过程中，这些结构 比序列更保守。通过比较多个同源序列，可以推断结构。 我们开发了TurboFold作为一种准确快速的自动序列比较方法， 保守的RNA二级结构和比对。我们还通过基于知识的 预测保守的非典型碱基对的潜力，这是三级结构的基础。 扩展我们的TurboFold方法，我们将开发新的高影响力算法和软件来解决 RNA生物学中的重要问题。首先，我们将开发新的工具来估计RNA的同源性， 使用序列之间的系统发育关系来更准确地预测结构和比对。 其次，我们将通过使用保守的非典型对的预测来改进三级结构建模 作为构建全原子模型的限制。第三，我们将开发新的工具， 二级和三级结构，其中存在来自相同家族的RNA序列的模板结构。