Multiple native-like RNA topologies and the corresponding relative free energy values are accessible from the iFoldRNA server. Our recent work has demonstrated the efficacy of the DMD conformational sampling engine in rapid simulations of RNA folding dynamics (Ding et al.
). The iFoldRNA resource enables world-wide access to rapid tertiary structure prediction and folding thermodynamics of RNA molecules using the DMD engine. Folding parameters including inter-nucleotide contact maps, simulation trajectories, gyration radii, root mean square deviations (RMSDs) from native state, and fraction of native-like contacts (Q
-value) are accessible from the iFoldRNA server. Secondary structures generated by iFoldRNA are consistent with Mfold and ViennaRNA predictions.
Low RMSDs (2–3 Å) are observed in 3D superpositions of iFoldRNA predictions against experimental structures, demonstrating the accuracy of iFoldRNA in structure prediction (a and b). Typical iFoldRNA folding simulations and analyses are performed within an hour (b) as compared to months to years spent on conventional molecular dynamics simulations to adequately explore the conformational space. Fast conformational sampling ability of DMD enables rapid structure prediction of putative RNA sequences using iFoldRNA. We have also developed a post-simulation analysis tool, iFoldRNA-Analysis available at the iFoldRNA website for user-specified analyses of RNA folding using the weighted histogram analysis method (http://www.mmtsb.org
). Sample simulation outputs obtained from iFoldRNA and iFoldRNA-Analysis are elucidated in c and d. Folding transition temperatures obtained from specific heat graph (c) and fractions of native base pairs (d) can be directly compared across different RNA sequence.
Fig. 1. iFoldRNA tertiary structure prediction and folding thermodynamics. (a) Superposition of iFoldRNA generated stem-loop (sticks) versus corresponding NMR structure (cartoon; Nucleic Acid DataBank: 1n8x; all-atom RMSD: 2.65 Å). (b) Scaling of iFoldRNA (more ...)
Large RNA molecules having >50 nt (e.g. ribosomal RNA, NDB: 2il9, 142 nt) require significantly longer time scales to sample the exponentially increasing conformational space. This limits the accuracy of the iFoldRNA structure prediction to intermediate-length RNA molecules (<50 nt). In future, experimental constraints, e.g. using SHAPE (Wilkinson et al.
) may be integrated with iFoldRNA to overcome such size limitations. We anticipate that the iFoldRNA server will gather significant attention in the research community interested in predicting 3D structures and probing folding mechanisms of RNA molecules. The iFoldRNA server is freely accessible at http://iFoldRNA.dokhlab.org
for academic and non-profit users.