Characterizing RNA Oligomers Using Stochastic Titration Constant-pH Metadynamics Simulations.

Area of Science:

• Computational chemistry
• Molecular dynamics
• Biophysics

Background:

• RNA flexibility is crucial for biological function, influenced by hydrogen bonding and protonation events.
• Constant pH molecular dynamics (CpHMD) methods are valuable for studying pH-dependent properties of biomolecules.
• pH-sensitive computational methods have been underexplored for nucleic acids, despite biological relevance.

Purpose of the Study:

• To extend the stochastic titration CpHMD method for RNA simulations.
• To validate the method's ability to capture nucleotide titration events in single-stranded RNAs.
• To integrate metadynamics for enhanced sampling of protonation-conformation coupling.

Main Methods:

• Extension of the stochastic titration CpHMD method with RNA parameters from the χOL3 AMBER force field.
• Validation using RNA trimers and pentamers with a single central titratable site.
• Integration of well-tempered metadynamics (CpH-MetaD) with PLUMED for improved sampling.

Main Results:

• The CpHMD method successfully captured titration events in single-stranded RNA nucleotides.
• pKa estimates from the CpH-MetaD approach agreed with experimental data.
• The method accurately reproduced electrostatic changes around titratable nucleobases in RNA.

Conclusions:

• The validated st-CpHMD method with metadynamics is a reliable tool for studying biologically relevant RNA systems.
• The findings provide molecular insights into factors affecting RNA pKa shifts.
• This approach advances the computational study of pH-sensitive RNA structures and functions.