Visualizing RNA Structures by SAXS-Driven MD Simulations

Weiwei He, Anja Henning-Knechtel, Serdal Kirmizialtin

Research output: Contribution to journalArticlepeer-review


The biological role of biomolecules is intimately linked to their structural dynamics. Experimental or computational techniques alone are often insufficient to determine accurate structural ensembles in atomic detail. We use all-atom molecular dynamics (MD) simulations and couple it to small-angle X-ray scattering (SAXS) experiments to resolve the structural dynamics of RNA molecules. To accomplish this task, we utilize a set of re-weighting and biasing techniques tailored for RNA molecules. To showcase our approach, we study two RNA molecules: a riboswitch that shows structural variations upon ligand binding, and a two-way junction RNA that displays structural heterogeneity and sensitivity to salt conditions. Integration of MD simulations and experiments allows the accurate construction of conformational ensembles of RNA molecules. We observe a dynamic change of the SAM-I riboswitch conformations depending on its binding partners. The binding of SAM and Mg2+ cations stabilizes the compact state. The absence of Mg2+ or SAM leads to the loss of tertiary contacts, resulting in a dramatic expansion of the riboswitch conformations. The sensitivity of RNA structures to the ionic strength demonstrates itself in the helix junction helix (HJH). The HJH shows non-monotonic compaction as the ionic strength increases. The physics-based picture derived from the experimentally guided MD simulations allows biophysical characterization of RNA molecules. All in all, SAXS-guided MD simulations offer great prospects for studying RNA structural dynamics.

Original languageEnglish (US)
Article number781949
JournalFrontiers in Bioinformatics
StatePublished - 2022


  • experimentally guided simulations
  • maximum entropy
  • MD simulation
  • RNA
  • SAXS (small-angle X-ray scattering)
  • structural modelling

ASJC Scopus subject areas

  • Biochemistry
  • Biotechnology
  • Computational Mathematics
  • Statistics and Probability
  • Structural Biology


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