Internet-scale discovery of RNA bioengineering rules

互联网规模发现RNA生物工程规则

• 批准号: 8668102
• 负责人: Rhiju Das
• 金额: $ 45.52万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-06-05 至 2016-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8668102
• 关键词: Adenine; Adoption; Algorithm Design; Algorithms; Anti-Bacterial Agents; Antiviral Therapy; Automobile Driving; Bacteria; Base Pairing; Benchmarking; Biomedical Computing; Biomedical Engineering; Chemicals; Communities; Computational algorithm; Computer Simulation; Computing Methodologies; Crowding; Data; Data Analyses; Databases; Development; Disease; Elements; Failure; Feedback; Functional RNA; Funding; Genetic; Glean; HIV; Human; In Vitro; Internet; Intuition; Knowledge; Life; Ligand Binding; Maps; Marketing; Masks; Methods; Mining; Modeling; Nanotechnology; Nucleic Acids; Nucleotides; Organism; Pattern; Performance; Play; Positioning Attribute; Publications; RNA; RNA Biochemistry; RNA Conformation; RNA Folding; RNA Sequences; RNA chemical synthesis; Research; Resolution; Retroviridae; Role; Science; Scientist; Seeds; Shapes; Social Network; Solutions; Source; Staging; Structure; Testing; Time; United States National Institutes of Health; Validation; Viral; base; cost; design; high throughput technology; insight; nanoengineering; neoplastic cell; next generation; novel; programs; repository; research study; sensor; success; tool; trend

DESCRIPTION (provided by applicant): Recent discoveries of biologically fundamental non-coding RNAs are inspiring novel antibacterial, antitumor, and antiviral therapies that might disable or manipulate the molecules involved. However, in silico folding models cannot yet confidently predict RNA conformations in vitro, slowing the development of these potentially life-saving efforts. To develop the next-generation of robust and rigorously tested RNA bioengineering rules, we are exploring an unconventional strategy: last year, we released a citizen science project enabling non-experts to develop and test folding hypotheses in internet-scale RNA design competitions that are rigorously scored through wet-lab feedback. Launched in early 2011, the 25,000-player EteRNA project already outperforms existing previous methods for designing novel RNA structures which fold properly in vitro. The critical next stage is to sustain and formalize the RNA nanoengineering insights preserved within the EteRNA community. We propose steps to consolidate the community's experimentally validated human computation into a suite of automated design algorithms (EteRNAbot) usable by the entire RNA nanoenginering community. Beyond compiling such cases, we will crowd-source the rigorous search and resolution of in silico and in vitro design failures with thousands of new experiments. Finally, we will deploy the EteRNA- 3D interface for both expert and crowd-sourced three-dimensional design, leveraging a growing database of 3D building blocks and the ROSETTA RNA folding/design algorithms. We will evaluate success in each aim via synthesis and single-nucleotide- resolution chemical mapping of novel designs through our high-throughput wet-lab pipeline. More generally, we will evaluate success by assessing the extent of utilization and citation of the automated design tools; the extent of mining and citation of the publically available RNA Mapping Database generated for the project; and the adoption of the EteRNA paradigm for Internet-scale scientific discovery in biomedical computation problems beyond nucleic acid design.

描述（由申请人提供）：生物学上基本非编码RNA的最新发现激发了新型抗菌，抗肿瘤和抗病毒疗法，这些抗病毒药物可能会禁用或操纵所涉及的分子。但是，在计算机折叠模型中，还不能自信地预测体外RNA构象，从而减慢了这些潜在的挽救生命的努力的发展。为了制定强大且严格测试的RNA生物工程规则的下一代，我们正在探索一种非常规的策略：去年，我们发布了一个公民科学项目，实现了非专家，可以在Internet规模的RNA设计中开发和测试折叠式假设，这些竞赛是通过Wet-Lab-Lab-Labbab Fefferback进行严格评分的。 25,000名玩家的Eterna项目于2011年初推出，已经胜过现有的现有方法，即设计新型RNA结构，这些方法在体外正确折叠。接下来的关键是维持和正式化RNA纳米工程学的见解。我们提出的步骤将整个RNA纳米工程社区可用的自动化设计算法（Eternabot）巩固社区经过实验验证的人类计算的步骤。除了汇编此类情况外，我们还将通过数千种新实验来群体群中的硅和体外设计失败的严格搜索和分辨率。最后，我们将为专家和众包三维设计部署Eterna-3D接口，利用不断增长的3D构建块和Rosetta RNA折叠/设计算法的数据库。我们将通过我们的高通量湿lab管道对新型设计的合成和单核苷酸分辨率映射来评估每个目标的成功。更普遍地，我们将通过评估自动化设计工具的利用程度和引用来评估成功；为该项目生成的公开可用RNA映射数据库的采矿和引用程度；以及在核酸设计以外的生物医学计算问题中采用Eterna范式来进行互联网规模的科学发现。