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

程序性核糖体移码对于许多病毒（包括HIV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。由于移码的调节已显示出显著影响病毒活力，RNA移码元件（FSE）已成为有吸引力的抗病毒药物靶标。然而，在治疗策略成功之前，必须了解框架转移的复杂方面。继2020年NSF RAPID奖之后，Schlick数学/计算生物学实验室与Laederach实验RNA组合作，将联合收割机图论应用于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和相关病毒的RNA FSE的结构和机制。合作研究计划将是学生和博士后研究员，包括妇女和少数民族，在数学，计算机科学，生物学，物理学，化学和工程，通过计算机程序开发，数据分析和生物学解释的跨学科培训的基础。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;开发模拟算法和粗粒度模型;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。该项目将描述SARS-CoV的FSE的构象和结构转变，2从系统发育和生物物理学的观点，利用数学RNA图的全球代表性。具体而言，研究人员将通过计算和实验验证SARS-CoV-2亲属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的转换途径，探索移码机制;识别并实验性地测试结构-通过RAG反向折叠和遗传算法改变突变以将FSE转化为复杂的交织基序以阻碍移码。这种独特的方法应用于冠状病毒（包括SARS-CoV-2）中的移码元件，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的见解，以解释病毒结构和移码效率/病毒活力之间的关系。通过从全局图论的角度来看待结构，模式可以比基于序列或原子的模型更容易被识别和关联。确定的结构、机制和改变结构的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。

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.