Flexibility of Short-Strand RNA in Aqueous Solution as Revealed by Molecular Dynamics Simulation: Are A-RNA and A′-RNA Distinct Conformational Structures?
Defang Ouyang A B , Hong Zhang B , Dirk-Peter Herten C , Harendra S. Parekh A and Sean C. Smith B DA School of Pharmacy, The University of Queensland, Brisbane, Qld 4072, Australia.
B Centre for Computational Molecular Science, Australian Institute of Bioengineering and Nanotechnology, The University of Queensland, Brisbane, Qld 4072, Australia.
C BIOQUANT, Universität Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany.
D Corresponding author. Email: s.smith@uq.edu.au
Australian Journal of Chemistry 62(9) 1054-1061 https://doi.org/10.1071/CH09090
Submitted: 13 February 2009 Accepted: 23 July 2009 Published: 17 September 2009
Abstract
We use molecular dynamics simulations to compare the conformational structure and dynamics of a 21-base pair RNA sequence initially constructed according to the canonical A-RNA and A′-RNA forms in the presence of counterions and explicit water. Our study aims to add a dynamical perspective to the solid-state structural information that has been derived from X-ray data for these two characteristic forms of RNA. Analysis of the three main structural descriptors commonly used to differentiate between the two forms of RNA – namely major groove width, inclination and the number of base pairs in a helical twist – over a 30 ns simulation period reveals a flexible structure in aqueous solution with fluctuations in the values of these structural parameters encompassing the range between the two crystal forms and more. This provides evidence to suggest that the identification of distinct A-RNA and A′-RNA structures, while relevant in the crystalline form, may not be generally relevant in the context of RNA in the aqueous phase. The apparent structural flexibility observed in our simulations is likely to bear ramifications for the interactions of RNA with biological molecules (e.g. proteins) and non-biological molecules (e.g. non-viral gene delivery vectors).
Acknowledgements
We acknowledge generous allocations of CPU time from the Australian National Computing Infrastructure (NCI) facility as well as from the computational molecular science cluster computing facility at The University of Queensland, funded in part by the Australian Research Council (ARC) Linkage, Infrastructure, Equipment and Facilities (LIEF) scheme (grant number LE0882357).
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