Non-coding (nc)RNAs are key players in biology and are increasingly recognized as targets to treat infectious diseases, cancer, and genetic disorders, and as molecular tools for bioengineering and synthetic biology. Functional and regulatory RNAs undergo conformational transitions in multi-step biochemical cycles, ligand binding, and signaling. It is important to understand how these RNA structures form and how they dynamically change in response to cellular and chemical cues because of the biological importance of these RNAs, because this understanding will provide tools for bio-engineering and may facilitate therapeutic intervention, and, most fundamentally, because RNA is an essential molecule of life, both present and past. The thermodynamics of RNA secondary structure formation can be predicted with reasonable accuracy from nearest neighbor rules, and there have been remarkable advances in determining 3D RNA and RNAprotein structures. However, we lack a predictive energetic model for RNA tertiary conformational thermodynamics, which is ultimately required to understand and manipulate RNA form and function in biological processes. Unlike the energetic additivity of base pair steps for RNA secondary structure energetics, RNA tertiary structure energetics requires the statistical mechanical modeling of conformational ensembles and determination of partition functions that delineate the probabilities of forming different conformations. RNA's molecular properties?hierarchical folding, repeating structural motifs, and sparse tertiary contact interfaces?render tertiary structure energetics far simpler and more tractable for RNA than for proteins. From these properties, a Reconstitution Model has been developed that could allow conformational thermodynamics to be predicted based on conformational ensembles of component structural elements: helices, junctions, and tertiary contact partners. The central hypothesis of this proposal is that, by characterizing conformational thermodynamics for the array of component parts, the conformational thermodynamics of any arbitrary RNA can be determined. The central goals of this proposal are to test and develop this model and to overcome the vast challenge of determining conformational ensembles for thousands of RNA element. To accomplish this, `RNA-MaP' will be used?a novel technology that provides millions of thermodynamic measurements and quantitative `thermodynamic fingerprints' for tens of thousands of RNA helix, junction, and tertiary contact elements and provides data to obtain conformational ensembles for each element. This project will (1) build an atlas of conformational thermodynamics for RNA elements; (2) define a roster of conformational ensembles for these elements; and then (3) use this information within the Reconstitution Model to design and rationally engineer the conformational and energetic properties of ncRNAs. This project will also provide a freely available computational tool, RNAMake-?G, to model and engineer dynamic RNA tertiary structures, and will provide a wealth of high-precision thermodynamic data to help guide community-wide model development.
RNA is the central component in gene expression, transmitting information from DNA's stored genetic code to proteins, but RNAs are also active participants in the control of gene expression, often acting as structured and dynamic entities. Aberrant RNA structure and complexes lead to dysregulation in human disease, and pathogens often use structured RNA molecules in their life cycles to alter normal host RNA function, highlighting the fundamental, pathophysiological, and translational implications of understanding the manner by which RNA sequence leads to biological function. While the conformational behaviors of many individual RNA molecules have been described, we aim to provide a means to predict the behaviors of any arbitrary RNA by creating an atlas of conformational ensembles of RNA structural elements?the building blocks of complex, biologically relevant RNAs?that ultimately will allow us to understand, manipulate, and engineer RNA conformational states and transitions from simple parts.
