Collaborative Research: Unraveling Structural and Mechanistic Aspects of RNA Viral Frameshifting Elements by Graph Theory and Molecular Modeling

程序性核糖体移框对于许多病毒（包括艾滋病毒和sars相关冠状病毒）来说是必不可少的，它可以翻译mRNA上重叠的阅读框，从而产生必需的病毒蛋白。由于帧移的调节已被证明能显著影响病毒的生存能力，RNA帧移元件（FSE）已成为一个有吸引力的抗病毒药物靶点。然而，在治疗策略取得成功之前，必须了解框架转移的复杂方面。继2020年NSF RAPID奖之后，Schlick数学/计算生物学实验室将与Laederach实验RNA小组合作，将图论应用于RNA （RAG: RNA- as - graphs）与生物物理研究和生物分子建模/模拟相结合，以揭示SARS-CoV-2及相关病毒RNA FSE的结构和机制。该合作研究项目将通过计算机程序开发、数据分析和生物解释，为学生和博士后（包括女性和少数族裔）在数学、计算机科学、生物、物理、化学和工程领域提供跨学科培训的基础。学生和博士后将学习分析、处理和可视化生物数据；设计和验证模型；开发仿真算法和粗粒度模型；并收集和解释结构/功能模式，以产生新的数学和生物物理关系。该项目将通过利用数学RNA图的全局表示，从系统发育和生物物理学的角度描述SARS-CoV-2的FSE的构象和结构转变。具体而言，研究人员将通过实验计算和验证SARS-CoV-2亲缘病毒FSE的RNA二级结构构象景观，深入了解冠状病毒FSE的进化路径；通过确定SARS-CoV-2 FSE的转移途径，探索框架转移机制；并通过RAG逆折叠和遗传算法识别和实验测试结构改变突变，将FSE转化为复杂的交织基序，以阻止帧移。这种独特的方法应用于包括SARS-CoV-2在内的冠状病毒的移帧元件，使用新的数学图论工具和生物物理模型，将对相关病毒的结构、机制和进化趋势产生重要见解，以解释病毒结构与移帧效率/病毒活力之间的关系。通过从全局图论的角度来看结构，可以比序列或基于原子的模型更容易地识别和关联模式。确定的结构、机制和结构改变突变定义了基因治疗和治疗干预的抗病毒靶点。该奖项反映了美国国家科学基金会的法定使命，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。

Programmed ribosomal frameshifting is indispensable to many viruses, including HIV and SARS-associated coronaviruses, to translate overlapping reading frames on the mRNA so that essential viral proteins can be produced. Because modulation of frameshifting has been shown to dramatically influence viral viability, the RNA frameshifting element (FSE) has been an attractive anti-viral drug target. However, the complex aspects of frameshifting must be understood before therapeutic strategies can succeed. Following a 2020 NSF RAPID award, the Schlick mathematics/computational biology lab, in collaboration with the Laederach experimental RNA group, will combine graph theory applications to RNA (RAG: RNA-As-Graphs) with biophysical studies and biomolecular modeling/simulation to unravel structures and mechanisms of the RNA FSE of SARS-CoV-2 and related viruses. The collaborative research program will be the basis for interdisciplinary training of students and postdoctoral fellows, including women and minorities, in mathematics, computer science, biology, physics, chemistry, and engineering, through computer program development, data analysis, and biological interpretations. Students and postdocs will learn to analyze, process, and visualize biological data; devise and validate models; develop simulation algorithms and coarse-grained models; and collect and interpret structural/functional patterns to yield new mathematical and biophysical relationships.The project will describe conformations and structural transitions of the FSE of SARS-CoV-2 from phylogenetic and biophysical viewpoints by exploiting global representation of mathematical RNA graphs. Specifically, the researchers will gain insight into the evolutionary path of the FSE of coronaviruses by computing and validating experimentally RNA secondary-structure conformational landscapes of the FSE of SARS-CoV-2 relatives; probe frameshifting mechanisms by determining the SARS-CoV-2 FSE's transition pathway; and identify and test experimentally structure-altering mutations to transform the FSE into complex intertwined motifs by RAG inverse folding and genetic algorithms to hamper frameshifting. This unique approach applied to frameshifting elements in coronaviruses including SARS-CoV-2 using novel mathematical graph-theory tools and biophysical models will yield crucial insights into the structure, mechanisms, and evolutionary trends in related viruses to explain the relationship between viral structure and frameshifting efficiency/viral viability. By looking at structure from a global graph theory point of view, patterns can be discerned and related more easily than sequence or atomic-based models. The determined structures, mechanisms, and structure-altering mutations define gene therapy and anti-viral targets for therapeutic interventions.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.