RAFFT: Efficient prediction of RNA folding pathways using the fast Fourier transform
Fig 7
Application of the folding kinetic ansatz on CFSE.
(A) Fast-folding graph in four steps and N = 20 structures stored in a stack at each step. The edges are coloured according to ΔΔG. At each step, the structures are ordered by their free energy from top to bottom. The minimum free energy structure found is at the top left of the graph. A unique ID annotates visited structures in the kinetics. For example, “59” is the ID of the MFE structure. (B) MFE (computed with RNAfold) and the native CFSE structure. (C)The change in structure frequencies over time. The simulation starts with the whole population in the open-chain or unfolded structure (ID 0). The native structure (Nat.l) is trapped for a long time before the MFE structure (MFE.l) takes over the population. (D) Folding landscape derived from the 68 distinct structures predicted using RAFFT. The axes are the components optimized by the MDS algorithm, so the base pair distances are mostly preserved. Observed structures are also annotated using the unique ID. MFE-like structures (MFE.l) are at the bottom of the figure, while native-like (Nat.l) are at the top.