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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.

COVID-19急需的治疗和疫苗依赖于对复杂病毒结构的基本理解。该项目将确定病毒RNA的两个区域的结构特性和药物结合潜力，这两个区域对于COVID-19基因组在宿主细胞中的入侵和繁殖至关重要：负责制造刺突蛋白和融合蛋白的基因。具体而言，该项目将开发新的、高效的基于图论的计算算法，用于识别COVID-19病毒基因组中的亚区域，这些亚区域在突变时改变了RNA的亚结构。这些亚区的鉴定将有助于发现抗病毒抑制剂化合物。PI实验室已经开发的图论工具为RNA结构分析和设计提供了粗粒度的方法。PI将联合收割机这些工具与生物分子建模相结合，以检查SARS，MERS和其他病毒已知的抗病毒抑制剂的治疗潜力。该项目将产生对RNA病毒区域的结构见解，并确定关键核苷酸和候选抑制剂，这将有助于在对抗COVID-19方面取得进展。这项研究对COVID-19以及未来可能出现的其他冠状病毒产生了深远的影响。该项目为包括妇女和少数民族在内的年轻科学家提供数学、生物学、化学和科学计算方面的独特跨学科培训。研究成果将迅速与COVID-19研究界分享。由于病毒基因组的高度序列和结构保守性以及CRISPR技术的快速出现，RNA靶向方法具有治疗潜力。当蛋白质抑制化合物导致RNA病毒基因组本身入侵时，它们也提供了替代方案。预期显著改变RNA结构的此类化合物可抑制病毒侵入和复制。由于融合蛋白编码区包含一个假结（交织的碱基对）的子结构参与移码机制，关键突变区域和相关的化合物，破坏这个假结的测定将是非常宝贵的。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。图论框架将在本项目中得到扩展和应用，以通过确定RNA COVID-19病毒基因组中的关键区域和相关化学抑制剂来应对COVID-19大流行，这些区域会干扰病毒融合到宿主细胞中并在宿主细胞内复制。通过该奖项，数学科学部的数学生物学项目和化学部的生命过程化学项目资助纽约大学的Schlick博士确定COVID-19病毒RNA的结构特性和药物结合潜力。该赠款是使用冠状病毒援助，救济，该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。