Elucidating kinetics and thermodynamics of RNA-ligand interactions using single molecule approaches

Project summary/abstract: Current understanding of and predictive models for folded RNA structures lag far behind our advances in protein folding. Yet recent work reveals the central role of RNA folds in diseases like viral infection, cancer and neurodegeneration. The potential to develop drugs against RNA targets causing illness is impeded by critical knowledge gaps in our understanding of the sequence-structure-function relationships of RNA polymers. Beyond structure, the role of fast fluctuations between the various conformations of RNA is being recognized as playing a bigger role in RNA than in amino acid function. Quantifying both shape and kinetics of RNA requires single molecule tools that can achieve millisecond time and nanometer distance resolution. Through this Maximizing Investigator Research Award (MIRA), the Kamenetska Lab will be supported in their continued efforts to develop such single molecule biophysical tools combined with machine learning approaches in order to expand our knowledge and understanding of the structural and kinetic properties of RNA. These optical tweezer force spectroscopy tools are uniquely suited to quantifying the full energy landscape profile of RNA structures that governs the dynamics of these molecules. Here I propose to use these methods, based on published results from my laboratory, to fill three critical knowledge gaps. First, I will investigate the effects on RNA mechanics and dynamics of non-specific interactions between nucleic acids, including RNA, with small molecules and ions present in mammalian cells. Second, I will build on our work on synthetic and modified RNA structures to systematically quantify the relationship between structure and folding energetics, generating data for training predictive models of RNA folding not currently available. Finally, I will build analytic methods and pursue structural and kinetic characterization of complex RNA tertiary structures with multiple conformations. My targets include SARS-CoV-2 viral genomic RNA implicated in viral gene regulation, telomeric and 5' untranslated regions (5' UTR) structures associated with cancer phenotypes.