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Elastic network models (ENMs) are valuable and efficient tools forcharacterizing the collective internal dynamics of proteins based on theknowledge of their native structures. The increasing evidence that thebiological functionality of RNAs is often linked to their innate internalmotions, poses the question of whether ENM approaches can be successfullyextended to this class of biomolecules. This issue is tackled here byconsidering various families of elastic networks of increasing complexityapplied to a representative set of RNAs. The fluctuations predicted by thealternative ENMs are stringently validated by comparison against extensivemolecular dynamics simulations and SHAPE experiments. We find that simulationsand experimental data are systematically best reproduced by either an all-atomor a three-beads-per-nucleotide representation (sugar-base-phosphate), with thelatter arguably providing the best balance of accuracy and computationalcomplexity.

Elastic network models for RNA: a comparative assessment with molecular dynamics and SHAPE experiments