RNA Conformational Fluctuations from Elastic Network Models: A Comparison with Molecular Dynamics and Shape Experiments

The role of ribonucleic acid (RNA) in molecular biology is shifting from a mere messenger between DNA and proteins to an important player in many cellular activities. The central role of RNA molecules calls for a precise characterization of their structural and dynamical properties. Nowadays, experiments can be efficiently complemented by computational approaches. Within this framework, elastic network models (ENMs) are valuable and efficient tools for characterizing the collective internal dynamics of biomolecules starting from the sole knowledge of their structures. The increasing evidence that the biological functionality of RNAs is often linked to their innate internal motions, poses the question of whether ENM approaches can be successfully extended to these biomolecules. This issue, which is still largely unexplored, is tackled here by considering various families of elastic networks for a representative set of RNAs. The large-scale motions predicted by the alternative ENMs are stringently validated by comparison against extensive molecular dynamics (MD) simulations and SHAPE experimental data. We propose a specific combination of three ENM centroids (sugar-base-phosphate) as an optimal compromise capable of reproducing simulations and experiments. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.