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Updated: Jul 18, 2026

Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes

Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes

Published on: January 16, 2016

Assessing RNA atomistic force fields via energy landscape explorations in implicit solvent.

Konstantin Röder¹, Samuela Pasquali²

¹Randall Centre for Cell & Molecular Biophysics, King's College London, London, SE1 1UL UK.

Biophysical Reviews

|August 5, 2024

Summary

This study introduces the computational energy landscape framework to evaluate RNA force fields. It compares five force fields for an RNA pseudoknot, revealing insights into folding pathways and excited states.

Keywords:

Energy landscapes Force fields RNA

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Area of Science:

Computational Biology
Structural Biology
Biophysics

Background:

Predicting RNA structure and dynamics is challenging due to limited experimental data and environmental sensitivity.
Several RNA-specific atomistic force fields exist, but their suitability for specific RNA molecules is unclear.

Purpose of the Study:

To propose and apply the computational energy landscape (EL) framework for evaluating RNA force fields.
To compare the performance of five different RNA force fields using the EL framework on a small RNA pseudoknot.

Main Methods:

Application of the computational energy landscape framework.
Molecular dynamics simulations using five RNA force fields in implicit solvent.
Analysis of predicted native states, metastable states, folding pathways, and excited states.

Main Results:

The EL framework provides complementary information to enhanced sampling simulations.
Comparison of five RNA force fields reveals differences in predicted native and metastable states.
Insights into RNA folding pathways and higher energy excited states were obtained.

Conclusions:

The computational energy landscape framework is a valuable tool for assessing RNA force fields.
This approach allows for the evaluation of force fields based on kinetics and experimental data on metastable states.