Control of RNA function by conformational design

• Applicant: Professorin Dr. Sabine Müller
• Co-Applicant: Professor Dr. Ivo Hofacker
• Subject Area: Biological and Biomimetic Chemistry
• Term: from 2011 to 2013
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 193437619

Over the past two decades RNA has become a major focus of research. The discovery of ribozymes, riboswitches and small noncoding RNAs being involved in a large number of cellular processes has led to much interest in the understanding of how RNA structure and conformation are linked to its function and how RNA function can be controlled by conformational design. Accordingly, it has become evident that more complex design targets are not amenable to manual sequence design, but require the use of computer based optimization methods. On the other hand, since even small errors in the energy model can significantly shift the balance between alternative conformations, computational RNA structure prediction is often not accurate enough to yield immediately functional RNA molecules. The computational models are, however, very efficiently able to reduce the search space to a small number of candidates that can be probed experimentally. By combining computer-aided prediction with wet lab experiments, we aim at developing protocols and software tools for the design of functional RNA molecules. In particular, three systems will be evaluated: (i) self-splicing and (ii) self-replicating RNAs derived from the hairpin ribozyme, and (iii) self-induced RNA switches. Design of the respective systems will build up on previous experimental work, and will be strongly guided and/or optimized by computational prediction of RNA folding kinetics, RNA complex formation and conformational distribution as an essential tool to successfully solve more complex design problems. In turn, experimental testing of the theoretical predictions will allow us to identify shortcomings of the computational models. Repeated rounds of modelling and testing will be used to iteratively refine model setup and parameters.

• DFG Programme: Research Grants
• International Connection: Austria