Modeling and design of complex RNA structures

复杂 RNA 结构的建模和设计

• 批准号: 10685534
• 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/10685534
• 关键词: 2019-nCoV; Acceleration; 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; Modeling; Molecular Conformation; Organism; Phylogenetic Analysis; Play; RNA; RNA Computations; RNA Folding; RNA Viruses; RNA vaccine; Research; Role; Science; Shipping; Structure; Syringes; Untranslated RNA; Vaccines; Viral; Virus Replication; Visualization; Work; biophysical model; crowdsourcing; design; experimental study; flexibility; genetic information; human disease; neoplastic cell; novel; pandemic disease; therapeutic genome editing; three dimensional structure; tool; transmission process; tumor

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.

项目概要 RNA 的不断发现及其在细胞和病毒机制中的关键作用 正在激发新型抗菌、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”缺乏生物物理学理解正在减慢 这些可能挽救生命的努力。一个关键的瓶颈是不适用 晶体学、核磁共振、系统发育分析和生化方法来确定 非编码 RNA 在其所有功能状态下的部分有序构象。到 为了解决这个瓶颈，我们将生物物理建模、电子显微镜、 高通量生化/测序实验、机器学习、湿实验室- 集成的众包和广泛的协作网络。目前的项目 举例说明我们针对 COVID-19 大流行采取的方法。使用我们的 Ribosolve 混合动力 结构确定管道中，我们发现许多部分 SARS-CoV-2 RNA 基因组形成明确的 3D 结构，其靶向 反义寡核苷酸抑制病毒复制。在 OpenVaccine 挑战赛中，我们 正在开发高度结构化的 COVID-19 mRNA 疫苗，具有足够的体外 稳定性使得 mRNA 在预装注射器中能够在全球范围内运输。此次新冠肺炎 (COVID-19) 研究受益于我们的敏捷方法和 MIRA 所提供的灵活性 支持;我们现在使用的许多计算和实验方法并不存在 在大流行之前。由于 RNA 对生命至关重要，因此解决了许多科学问题 如果我们能够想象并解决人类疾病中的进一步“重大问题” 设计任何RNA。我的实验室致力于创建 RNA 计算和实验 基金会需要帮助我们所有人在未来几年实现这一目标。

项目成果

Using Rosetta for RNA homology modeling.

• DOI: 10.1016/bs.mie.2019.05.026
• 发表时间: 2019
• 期刊: Methods in enzymology
• 作者: Watkins AM;Rangan R;Das R
• 通讯作者: Das R

RNA secondary structure packages evaluated and improved by high-throughput experiments.

• DOI: 10.1038/s41592-022-01605-0
• 发表时间: 2022-10
• 期刊: NATURE METHODS
• 影响因子: 48
• 作者: Wayment-Steele, Hannah K.;Kladwang, Wipapat;Strom, Alexandra I.;Lee, Jeehyung;Treuille, Adrien;Becka, Alex;Das, Rhiju
• 通讯作者: Das, Rhiju

Learning RNA structure prediction from crowd-designed RNAs.

• DOI: 10.1038/s41592-022-01607-y
• 发表时间: 2022-10
• 期刊: NATURE METHODS
• 影响因子: 48
• 作者: Wayment-Steele, Hannah K.;Das, Rhiju
• 通讯作者: Das, Rhiju

How to Kinetically Dissect an RNA Machine.

• DOI: 10.1021/acs.biochem.1c00392
• 发表时间: 2021-11-23
• 期刊: Biochemistry
• 影响因子: 2.9
• 作者: Das R;Russell R
• 通讯作者: Russell R

Three-dimensional structure-guided evolution of a ribosome with tethered subunits.

• DOI: 10.1038/s41589-022-01064-w
• 发表时间: 2022-09
• 期刊: NATURE CHEMICAL BIOLOGY
• 影响因子: 14.8
• 作者: Kim, Do Soon;Watkins, Andrew;Bidstrup, Erik;Lee, Joongoo;Topkar, Ved;Kofman, Camila;Schwarz, Kevin J.;Liu, Yan;Pintilie, Grigore;Roney, Emily;Das, Rhiju;Jewett, Michael C.
• 通讯作者: Jewett, Michael C.