RNA's have been shown to readily adopt a variety of unique and irregular structures which allow them to perform a wide variety of biochemical tasks such as gene regulation, enzymatic catalysis, and metabolite sensing. The versatility and modularity of these naturally occurring RNA machines hint that they could potentially be turned into extremely powerful bio-nanotechnological tools in the near future. However, we cannot hope to design novel RNAs unless we first understand the mechanism by which an RNA sequence chooses its unique three-dimensional fold. While informatics-based approaches have proved extremely successful for predicting RNA secondary structure given its sequence (that is, Watson-Crick base pairing), there is no equivalent heuristic that can predict the non-canonical motifs and tertiary interactions that characterize functional RNAs.
The Garcia lab is interested in the use of accurate, all-atom computer simulations of small, model RNA systems to address these gaps in our understanding of RNA folding. We are developing advanced-sampling techniques and kinetic clustering algorithms to identify the intermediate steps that unfolded RNAs must transverse in order to arrive at the final, folded structure. Finally, we are also working to improve the underlying RNA force-field parameters themselves, which are considerably less mature than their protein-centric counterparts.