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

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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.