Ab initio RNA folding by discrete molecular dynamics: from structure prediction to folding mechanisms.
RNA molecules with novel functions have revived interest in the accurate prediction of RNA three-dimensional (3D) structure and folding dynamics. However, existing methods are inefficient in automated 3D structure prediction. Here, we report a robust computational approach for rapid folding of RNA molecules. We develop a simplified RNA model for discrete molecular dynamics (DMD) simulations, incorporating base-pairing and base-stacking interactions. We demonstrate correct folding of 150 structurally diverse RNA sequences. The majority of DMD-predicted 3D structures have <4 A deviations from experimental structures. The secondary structures corresponding to the predicted 3D structures consist of 94% native base-pair interactions. Folding thermodynamics and kinetics of tRNA(Phe), pseudoknots, and mRNA fragments in DMD simulations are in agreement with previous experimental findings. Folding of RNA molecules features transient, non-native conformations, suggesting non-hierarchical RNA folding. Our method allows rapid conformational sampling of RNA folding, with computational time increasing linearly with RNA length. We envision this approach as a promising tool for RNA structural and functional analyses.
Ding
Feng
F
Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA.
Sharma
Shantanu
S
Chalasani
Poornima
P
Demidov
Vadim V
VV
Broude
Natalia E
NE
Dokholyan
Nikolay V
NV
D001483:Base Sequence; D019295:Computational Biology / Q000379:methods*; D008956:Models, Chemical; D008969:Molecular Sequence Data; D009690:Nucleic Acid Conformation; D012313:RNA / Q000737:chemistry*; D013816:Thermodynamics
D012313:RNA