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.

项目总结