Modeling and design of complex RNA structures

复杂 RNA 结构的建模和设计

基本信息

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
项目类别：
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

项目摘要

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。

项目成果

期刊论文数量（19）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Using Rosetta for RNA homology modeling.

DOI：
10.1016/bs.mie.2019.05.026
发表时间：
2019
期刊：
Methods in enzymology
影响因子：
0
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.