Modeling and design of complex RNA structures

复杂 RNA 结构的建模和设计

• 批准号: 10405315
• 负责人: Rhiju Das
• 金额: $ 68.47万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10405315
• 关键词: 2019-nCoV; Address; Anti-Bacterial Agents; Antisense Oligonucleotides; Bacteria; Biochemical; Biomedical Research; Biophysics; Brain; COVID-19; COVID-19 pandemic; Complex; Crystallography; Development; Disease; Electron Microscopy; Foundations; Genome; HIV; Hybrids; In Vitro; Life; Machine Learning; Messenger RNA; Methods; Molecular Conformation; Organism; Phylogenetic Analysis; Play; RNA; RNA Computations; RNA Folding; RNA Viruses; RNA vaccine; Research; Role; Savings; Science; Shipping; Structure; Syringes; Untranslated RNA; Vaccines; Viral; Virus Replication; Work; biophysical model; crowdsourcing; design; experimental study; flexibility; genetic information; human disease; model design; neoplastic cell; novel; pandemic disease; therapeutic genome editing; three dimensional structure; tool

PROJECT SUMMARY The continuing discoveries of RNAs and their critical roles in cellular and viral machinery are inspiring novel antibacterial, antitumor, antiviral, and genome-editing therapies based on disabling, manipulating, and repurposing the RNAs involved. Unfortunately, our poor biophysical understanding of `how RNAs work' is slowing the development of these potentially life-saving efforts. A critical bottleneck has been the inapplicability of crystallography, NMR, phylogenetic analysis, and biochemical methods to determine the partly ordered conformations of non-coding RNAs in all their functional states. To address this bottleneck, we bring together biophysical modeling, electron microscopy, high throughput biochemical/sequencing experiments, machine learning, wet-lab- integrated crowdsourcing, and a wide collaborative network. Current projects that exemplify our approach involve the COVID-19 pandemic. With our Ribosolve hybrid structure determination pipeline, we are discovering that numerous segments of the SARS-CoV-2 RNA genome form well-defined 3D structures whose targeting by antisense oligonucleotides inhibits viral replication. In the OpenVaccine challenge, we are developing highly structured COVID-19 mRNA vaccines with sufficient in vitro stability to enable world-wide shipping of mRNA in prefilled syringes. This COVID-19 research has benefited from our agile approach and the flexibility allowed by MIRA support; many of the computational and experimental methods we use now did not exist before the pandemic. Because RNA is so fundamental to life, tackling many of science's further `big questions' in human disease could be accelerated if we could visualize and design any RNA. My lab seeks to create the RNA computational and experimental foundation needed to get all of us there in upcoming years.

项目摘要 RNA的持续发现及其在细胞和病毒机械中的关键作用 鼓舞了新颖的抗菌，抗肿瘤，抗病毒和基因组编辑疗法 基于禁用，操纵和重新利用所涉及的RNA。很遗憾， 我们对“ RNA如何工作”的生物物理不良理解正在减缓的发展 这些潜在的挽救生命的努力。关键的瓶颈是 晶体学，NMR，系统发育分析和生化方法，以确定 在其所有功能状态下，部分有序的非编码RNA构象。到 解决这个瓶颈，我们将生物物理建模，电子显微镜汇总在一起， 高通量生化/测序实验，机器学习，湿lab- 集成的众包和广泛的协作网络。当前的项目 举例说明我们的方法涉及19009年大流行。与我们的Ribosolve混合动力 结构确定管道，我们发现 SARS-COV-2 RNA基因组形成了明确定义的3D结构，其靶向由 反义寡核苷酸抑制病毒复制。在OpenVaccine挑战中，我们 正在开发高度结构化的互联-19 mRNA疫苗，并有足够的体外 稳定性，可以在预灌注的注射器中全球跨越mRNA的运输。这次Covid-19 研究受益于我们的敏捷方法和Mira允许的灵活性 支持;我们现在使用的许多计算和实验方法都不存在 在大流行之前。因为RNA对生活如此重要，所以解决了许多科学的 如果我们可以看到和 设计任何RNA。我的实验室试图创建RNA计算和实验性 基金会需要在接下来的几年中将我们所有人带到那里。