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Sci Rep. 2017 Apr 10;7:45812. doi: 10.1038/srep45812.

Capturing RNA Folding Free Energy with Coarse-Grained Molecular Dynamics Simulations.

Author information

1
Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas 78712, United States.
2
Department of Physics, University of Texas at Austin, Austin, Texas 78712, United States.

Abstract

We introduce a coarse-grained RNA model for molecular dynamics simulations, RACER (RnA CoarsE-gRained). RACER achieves accurate native structure prediction for a number of RNAs (average RMSD of 2.93 Å) and the sequence-specific variation of free energy is in excellent agreement with experimentally measured stabilities (R2 = 0.93). Using RACER, we identified hydrogen-bonding (or base pairing), base stacking, and electrostatic interactions as essential driving forces for RNA folding. Also, we found that separating pairing vs. stacking interactions allowed RACER to distinguish folded vs. unfolded states. In RACER, base pairing and stacking interactions each provide an approximate stability of 3-4 kcal/mol for an A-form helix. RACER was developed based on PDB structural statistics and experimental thermodynamic data. In contrast with previous work, RACER implements a novel effective vdW potential energy function, which led us to re-parameterize hydrogen bond and electrostatic potential energy functions. Further, RACER is validated and optimized using a simulated annealing protocol to generate potential energy vs. RMSD landscapes. Finally, RACER is tested using extensive equilibrium pulling simulations (0.86 ms total) on eleven RNA sequences (hairpins and duplexes).

PMID:
28393861
PMCID:
PMC5385882
DOI:
10.1038/srep45812
[Indexed for MEDLINE]
Free PMC Article

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