Force field dependence of riboswitch dynamics.

Area of Science:

• Computational Biology
• Biochemistry
• Molecular Biophysics

Background:

• Riboswitches are noncoding RNA regulatory elements controlling gene expression.
• Understanding the apo state dynamics of riboswitch aptamer domains is essential for characterizing metabolite binding mechanisms.
• Molecular dynamics (MD) simulations offer atomistic insights into RNA dynamics, but force field accuracy is a concern.

Purpose of the Study:

• To evaluate the accuracy of contemporary molecular dynamics force fields in simulating the structural dynamics of riboswitch aptamer domains.
• To determine the influence of different Amber force field versions (ff99 vs. ff10) on the dynamics of the guanine-sensing riboswitch (Gsw) aptamer.
• To assess the impact of Mg2+ ions on Gsw aptamer dynamics and force field performance.

Main Methods:

• Performed 58 molecular dynamics (MD) simulations totaling over 11 microseconds.
• Utilized the Amber force field ff99 and its modified version ff10, with careful modeling of Mg2+ ions.
• Compared simulation results with experimental observations, including structural dynamics of wild-type and mutant Gsw aptamer domains.

Main Results:

• Amber ff99 demonstrated better agreement with experimental data on Gsw aptamer dynamics, including the influence of Mg2+.
• Amber ff10 exhibited overly damped motions and excessively stable tertiary interactions, likely due to excessive stabilization of the chi-anti region.
• Crystal structure analysis supported these findings, revealing high-anti chi torsions in mobile regions of the Gsw aptamer.

Conclusions:

• The Amber ff99 force field is more suitable for simulating the dynamics of marginally stable RNA systems like riboswitch aptamers compared to ff10.
• Force fields that overly stabilize certain RNA regions can dampen functionally relevant dynamics.
• Future RNA force field development should prioritize accurate representation of dynamics alongside structural characteristics, especially for marginally stable systems.