Poster abstracts
Poster number 41 submitted by Aaron Frank
Constructing conformational ensembles of RNA using solvent accessibility data
Jingru Xie (Department of Physics, University of Michigan), Aaron T. Frank (Departments of Biophysics and Chemistry, University of Michigan)
Abstract:
Experimental techniques such as nuclear magnetic resonance (NMR) spectroscopy, mass spectroscopy (MS), and chemical probing, can be used to interrogate the local solvent accessibility in ribonucleic acids (RNAs). Here, we used computational experiments to quantify the extent to which local solvent accessibility data can be used to reconstruct native conformational ensembles of RNAs. To accomplish this, we constructed pairs of decoy and target ensembles (i.e., simulated native ensembles)for a set of benchmark single-stranded RNAs and then reweighted the decoy ensembles using ensemble-averaged SASA data that we calculated from the target ensembles. We then quantified the extent to which the conformational distributions in the target ensembles resembled the target ensembles. In general, we found that given a set of ensemble-averaged SASA data, we could reweight the decoy ensemble such that the reweighted were “closer” to target than were the decoy ensembles. The ability to reconstruct ensembles is shown, however, to be sensitive to errors in the SASA data, which, in a practical sense, limits the overall “constraining” power of SASA data. This limitation notwithstanding, our results should pave the way for the direct utilization of experimentally-derived solvent accessibility data to construct dynamical ensembles of RNA.
Keywords: Reweighting, Solvent Accessibility, Conformational Ensembles