  A full understanding of RNA-mediated biology would require the knowledge of
three-dimensional (3D) structures, structural flexibility and stability of
RNAs. To predict RNA 3D structures and stability, we have previously proposed a
three-bead coarse-grained predictive model with implicit salt/solvent
potentials. In this study, we will further develop the model by improving the
implicit-salt electrostatic potential and involving a sequence-dependent
coaxial stacking potential to enable the model to simulate RNA 3D structure
folding in divalent/monovalent ion solutions. As compared with the experimental
data, the present model can predict 3D structures of RNA hairpins with
bulge/internal loops (<77nt) from their sequences at the corresponding
experimental ion conditions with an overall improved accuracy, and the model
also makes reliable predictions for the flexibility of RNA hairpins with bulge
loops of different length at extensive divalent/monovalent ion conditions. In
addition, the model successfully predicts the stability of RNA hairpins with
various loops/stems in divalent/monovalent ion solutions.

Biological Physics;Soft Condensed Matter;Chemical Physics;Computational Physics