RAPID: Exploring Covid-19 RNA Viral Targets By Graph-Theory-Based Modeling

RAPID：通过基于图论的建模探索 Covid-19 RNA 病毒靶点

基本信息

批准号：
2030377
负责人：
Tamar Schlick
金额：
$ 20万
依托单位：
New York University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-05-15 至 2022-04-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2030377&HistoricalAwards=false
关键词：
RAPID Exploring Covid 19 RNA

项目摘要

The urgently needed treatments and vaccines for COVID-19 rely on a fundamental understanding of the complex viral apparatus. This project will determine the structural properties and drug-binding potential of two regions of the viral RNA essential for invasion and propagation of the COVID-19 genome in host cells: genes responsible for making spike and fusion proteins. Specifically, the project will develop new and efficient graph-theory based computational algorithms for identifying subregions in the COVID-19 viral genome that alter the RNA substructure when they are mutated. Identification of these subregions will aid in the discovery of anti-viral inhibitor compounds. Graph theory tools already developed in the PI’s lab offer coarse-grained approaches for RNA structural analysis and design. The PI will combine these tools with biomolecular modeling to examine the therapeutic potential of anti-viral inhibitors known from SARS, MERS, and other viruses. This project will produce structural insights into the RNA viral regions and identify critical nucleotides and candidate inhibitors that will help make progress against COVID-19. The research has profound impact to COVID-19 as well as other coronaviruses that could emerge in the future. The project offers unique interdisciplinary training in mathematics, biology, chemistry, and scientific computing for young scientists, including women and minorities. The research results will be shared rapidly with the COVID-19 research community at large.RNA-targeting approaches have therapeutic potential due to the high sequence and structure conservation of the viral genomes and the rapid emergence of CRISPR technology. They also present alternatives when protein-inhibiting compounds lead to invasion of the RNA viral genome itself. Such compounds that alter the RNA structure significantly are expected to inhibit viral invasion and replication. Because the fusion-protein coding region contains a pseudoknot (intertwined base-pair) substructure involved in a frame-shifting mechanism, the determination of critical mutation regions and associated compounds that destroy this pseudoknot will be invaluable. The project team has rich experience in biomolecular modeling and simulation of nucleic acid complexes and has developed a graph-theory framework for analyzing RNA motifs, predicting structures, and designing novel RNA folds. The graph-theory framework will be extended and applied in this project to address the COVID-19 pandemic by determining key regions in the RNA COVID-19 viral genome and associated chemical inhibitors that would interfere with viral fusion into and replication within host cells. With this award, the Mathematical Biology Program in the Division of Mathematical Sciences and the Chemistry of Life Processes Program in the Division of Chemistry are funding Dr. Schlick from New York University to determine the structural properties and drug-binding potential of the COVID-19 viral RNA.This grant is being awarded using funds made available by the Coronavirus Aid, Relief, and Economic Security (CARES) Act supplemental funds allocated to MPS.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

迫切需要的 COVID-19 治疗方法和疫苗依赖于对复杂病毒装置的基本了解。该项目将确定对 COVID-19 的入侵和传播至关重要的病毒 RNA 的两个区域的结构特性和药物结合潜力。宿主细胞中的基因组：负责制造刺突蛋白和融合蛋白的基因，具体来说，该项目将开发基于图论的新型计算算法，用于识别 COVID-19 病毒基因组中发生突变时会改变 RNA 亚结构的子区域。其中PI实验室已经开发的图论工具将有助于发现抗病毒抑制剂化合物，为RNA结构分析和设计提供粗粒度的方法。PI将把这些工具与生物分子模型结合起来，以检查抗病毒抑制剂的治疗潜力。 -来自 SARS、MERS 和其他病毒的已知病毒抑制剂该项目将深入了解 RNA 病毒区域，并确定有助于在抗击 COVID-19 方面取得进展的关键核苷酸和候选抑制剂。该项目为包括女性和少数族裔在内的年轻科学家提供数学、生物学、化学和科学计算方面独特的跨学科培训，研究成果将与新冠病毒快速共享。 -19 整个研究界。由于病毒基因组的高度序列和结构保守性以及 CRISPR 技术的迅速出现，RNA 靶向方法具有治疗潜力，当蛋白质抑制化合物导致 RNA 病毒入侵时，它们也提供了替代方案。这些改变基因组本身的化合物。 RNA结构有望抑制病毒入侵和复制，因为融合蛋白编码区含有参与移码机制的假结（相互缠绕的碱基对）子结构，因此确定了破坏该假结的关键突变区域和相关化合物。该项目团队在核酸复合物的生物分子建模和模拟方面拥有丰富的经验，并开发了用于分析RNA基序、预测结构和设计新型RNA折叠的图论框架。在该项目中得到扩展和应用，通过确定 RNA COVID-19 病毒基因组中的关键区域以及干扰病毒在宿主细胞内融合和复制的关键区域来应对 COVID-19 大流行。数学科学系的项目和化学系的生命过程化学项目正在资助纽约大学的 Schlick 博士，以确定 COVID-19 病毒 RNA 的结构特性和药物结合潜力。这笔资助正在使用资金授予由分配给 MPS 的冠状病毒援助、救济和经济安全 (CARES) 法案补充资金提供。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（4）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

ANERGY TO SYNERGY-THE ENERGY FUELING THE RXCOVEA FRAMEWORK

从无能到协同——为 RXCOVEA 框架提供动力的能量

DOI：
10.1615/intjmultcompeng.2020035097
发表时间：
2020-01
期刊：
International Journal for Multiscale Computational Engineering
影响因子：
1.4
作者：
Bischof, Evelyne;Broek, Jantine A.C.;Cantor, Charles R.;Duits, Ashley J.;Ferro, Alfredo;Gao, Hillary W.;Li, Zilong;de Maria, Stella Luna;Maria, Naomi I.;Mishra, Bud;et al
通讯作者：
et al

A Fiedler Vector Scoring Approach for Novel RNA Motif Selection

用于新 RNA 基序选择的 Fiedler 矢量评分方法

DOI：
10.1021/acs.jpcb.0c10685
发表时间：
2021-02
期刊：
The Journal of Physical Chemistry B
影响因子：
0
作者：
Zhu, Qiyao;Schlick, Tamar
通讯作者：
Schlick, Tamar

To Knot or Not to Knot: Multiple Conformations of the SARS-CoV-2 Frameshifting RNA Element

打结还是不打结：SARS-CoV-2 移码 RNA 元件的多种构象

DOI：
10.1021/jacs.1c03003
发表时间：
2021-08
期刊：
Journal of the American Chemical Society
影响因子：
15
作者：
Schlick, Tamar;Zhu, Qiyao;Dey, Abhishek;Jain, Swati;Yan, Shuting;Laederach, Alain
通讯作者：
Laederach, Alain

Structure-altering mutations of the SARS-CoV-2 frameshifting RNA element

SARS-CoV-2 移码 RNA 元件的结构改变突变