A Multiscale Approach to RNA 3D Structure Prediction

Abstract

One of the key issues in the theoretical prediction of RNA stability and structure is how to predict the loop free energy. Experimental results have shown strong sequence-dependence of the loop free energy. However, most currently available models only account for the loop length-dependence of the loop free energy. We recently developed a three-bead coarse-grained model to generate the three-dimensional conformations for RNA hairpin loops. Based on the pseudo-torsion angles for the coarse-grained structures, we can extract a set of pseudo-torsion angle-based statistical potential parameters from the known structures. The statistical potential parameters enable folding predictions of the low-energy coarse-grained 3D structures from the sequence. Further molecular dynamics computations for an ensemble of decoy conformations about the predicted coarse-grained structures lead to the final all-atom structures. A notable advantage of the approach is the use of the statistical potential for evaluating the loop free energies and guiding the search for the low-energy coarse-grained structures from the sequence.