RNA 3D Structure Prediction by Using a Coarse-Grained Model and Experimental Data

RNAs form complex secondary and three-dimensional structures, and their biological functions highly rely on their structures and dynamics. Here we developed a general coarse-grained framework for RNA 3D structure prediction. A new, hybrid coarse-grained model that explicitly describes the electrostatics and hydrogen-bond interactions has been constructed based on experimental structural statistics. With the simulated annealing simulation protocol, several RNAs of less than 30-nt were folded to within 4.0 Å of the native structures. In addition, with limited restraints on Watson?Crick basepairing based on the data from NMR spectroscopy and small-angle X-ray scattering (SAXS) information, the current model was able to characterize the complex tertiary structures of large size RNAs, such as 5S ribosome and U2/U6 snRNA. We also demonstrated that the pseudoknot structure was better captured when the coordinating Mg2+ cations and limited basepairing restraints were included. The accuracy of our model has been compared favorably with other RNA structure prediction methods presented in the previous study of RNA-Puzzles. Therefore the coarse-grained model presented here offers a unique approach for accurate prediction and modeling of RNA structures.