Title: Development of simulation techniques to study co-transcriptional RNA nanostructure folding

The aim of the project is to use multi-scale simulation methods to explore the kinetics of co-transcriptional RNA folding, leading to new methods of RNA nanostructure design.

Understanding the physics of biomolecular folding is a key challenge of theoretical biophysics. DNA nanostructures are assembled by annealing multiple oligonucleotides with predictable base-pairing interactions: 3D structures with >104 components can be created by rational design. In contrast, recent progress in predicting protein folding by the Alphafold2 team from Google DeepMind required input from biophysics, bioinformatics and machine learning. Co-transcriptional folding of RNA nanostructures combines the single-strand architecture of proteins with relatively predictable interactions between nucleobases and is thus a fascinating model system.

Co-transcriptional folding has rich non-equilibrium physics: assembly during production of the polymer locks in metastable sub-structures. For example, formation of a double helix requires the wrapping of two strands around each other which, unless very short, is only possible if a free end is available (normally the case in multi-stranded assembly) or if the entire section is able to rotate freely. Tertiary contacts which prevent wrapping can lead to topological barriers to assembly. Key to the success of single-stranded folding is therefore control of the order of assembly of sub-structures. When a time-dependent annealing temperature is used, as is typical in DNA nanostructure assembly, order is controlled by the relative stabilities of the different elements. Under the isothermal conditions of co-transcriptional assembly one must instead exploit the order of synthesis to control assembly through design of free-energy barriers and non-equilibrium assembly pathways. To design non-equilibrium assembly pathways for nanostructure assembly we need design tools based on better understanding of the physics of co-transcriptional folding.

So far, relatively simple tools have been used to understand co-transcriptional assembly. We will use the coarse-grained oxRNA model to provide more detail of free-energy landscapes for assembly and how these can be sculpted to optimize assembly pathways. oxRNA represents each nucleotide as a single rigid body with interactions parametrized empirically to reproduce structural, mechanical and thermodynamic properties of single- and double-stranded RNA. This efficient representation enables study of large structures (>104 bases) as well as rare processes such as the formation or breaking of base pairs and strand displacement. oxRNA successfully reproduces some common motifs used in RNA nanotechnology e.g. kissing loops and PX crossovers. In designing synthetic RNA nanostructures we will focus on canonical base pairing, avoiding the many non-canonical structural motifs found in biological RNA, which hugely simplifies modelling and study of folding.

Fundamental insights obtained using folding simulations will be used to create and refine design tools to improve yield and to extend the size range over which co-transcriptional RNA origami nanostructures form reliably. This project will lay the foundations for the development of intracellular RNA nanostructure fabrication. Potential applications of self-assembled nanostructures within the cell include: probes of cellular function to report on cellular processes; in situ drug synthesis; intervention in natural genetic control systems or gene editing; and as a new generation of autonomous medical device, combining diagnosis and treatment with sub-cellular resolution.

This project lies within cross-council priority area Synthetic Biology. It integrates research in (EPSRC) Physical Sciences - Biophysics and Soft Matter Physics.

The project is supervised byProf. Andrew Turberfield and Prof. Ard Louis (Oxford Physics) and will involve close collaboration Prof. Jonathan Doye (Oxford Chemistry) and Prof. Petr Sulc (ASU).