Combining Simulations and Solution Experiments as a Paradigm for RNA Force Field Refinement.

Area of Science:

• Computational Chemistry
• Biophysics
• Structural Biology

Background:

• Current molecular dynamics potential energy models lack accuracy for RNA oligomer conformational ensembles.
• Existing models necessitate integration with experimental data for improved simulations.

Purpose of the Study:

• To develop a robust method for combining molecular dynamics simulations with bulk experimental data.
• To refine RNA force fields by incorporating experimental constraints and improving accuracy.
• To establish a new paradigm for self-consistent force field refinement.

Main Methods:

• A maximum entropy principle-based scheme was developed to merge simulation data with experimental observables.
• The method explicitly accounts for noise in both experimental measurements and forward models.
• The approach was validated using RNA nucleosides, dinucleosides, and tetranucleotides.

Main Results:

• Chemically consistent corrections were generated for the Amber RNA force field.
• The refined force field accurately reproduced experimental data for nucleosides and dinucleosides.
• Corrections demonstrated high transferability, showing unprecedented agreement with tetranucleotide data.

Conclusions:

• The proposed method effectively combines simulations and experiments for accurate RNA force field refinement.
• This approach offers a self-consistent framework for enforcing multiple experimental data points across various systems.
• The findings suggest a novel paradigm for developing more reliable molecular dynamics force fields.