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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.

项目总结

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.