HB-CUFIX: Force field for accurate RNA simulations

Accurate modeling of the dynamic structures of ribonucleic acid (RNA) molecules is essential for understanding their biological roles. However, such modeling remains challenging due to limitations in current force fields. This study critically evaluates three RNA force fields, HB-CUFIX, AMBER-χOL3, and AMBER-ROC, comparing their performance against experimental nuclear magnetic resonance and small-angle x-ray scattering data for single-stranded oligonucleotides. Using enhanced sampling techniques, specifically Unified Free Energy Dynamics, we exhaustively sampled the conformational space of tetramer and hexamer RNA sequences, achieving a detailed and thermodynamically converged view of their structural dynamics. Our findings reveal that HB-CUFIX outperforms AMBER-χOL3 and AMBER-ROC, providing near-experimental accuracy in capturing sequence-dependent structural preferences. In particular, HB-CUFIX accurately predicts low energy states for the AAAA and CCCC sequences, favoring A-form helical conformations, while the UUUU sequence adopts an extended, heterogeneous structure. The mixed GACC sequence displays a predominantly A-form helix with flexible terminal residues. These results highlight the significant role of sequence in dictating RNA conformational spaces, which are driven by base stacking interactions and covalent geometry. We also emphasize the importance of enhanced sampling, particularly methods that can handle large numbers of collective variables, in evaluating RNA force fields, as traditional brute-force Molecular dynamics fails to capture the conformational diversity of flexible RNAs. Our study provides a reliable tool for RNA structure prediction and dynamic analysis, supporting future advancements in RNA-targeted research and therapeutic design.

Authors

Institutions

Publication Details

Journal
The Journal of Chemical Physics
Published
2025-05-23
DOI
https://doi.org/10.1063/5.0249905
Citations
4
Primary Topic
RNA and protein synthesis mechanisms
Type
article
Field-Weighted Citation Impact
3.22

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

HB-CUFIX: Force field for accurate RNA simulations

Serdal Kırmızıaltın, Akshaya Kumar Das, Mark E. Tuckerman
4 citations
The Journal of Chemical Physics
RNA and protein synthesis mechanisms
3.22
article

HB-CUFIX: Force field for accurate RNA simulations

Serdal Kırmızıaltın, Akshaya Kumar Das, Mark E. Tuckerman
article en
4 citations

Abstract

Accurate modeling of the dynamic structures of ribonucleic acid (RNA) molecules is essential for understanding their biological roles. However, such modeling remains challenging due to limitations in current force fields. This study critically evaluates three RNA force fields, HB-CUFIX, AMBER-χOL3, and AMBER-ROC, comparing their performance against experimental nuclear magnetic resonance and small-angle x-ray scattering data for single-stranded oligonucleotides. Using enhanced sampling techniques, specifically Unified Free Energy Dynamics, we exhaustively sampled the conformational space of tetramer and hexamer RNA sequences, achieving a detailed and thermodynamically converged view of their structural dynamics. Our findings reveal that HB-CUFIX outperforms AMBER-χOL3 and AMBER-ROC, providing near-experimental accuracy in capturing sequence-dependent structural preferences. In particular, HB-CUFIX accurately predicts low energy states for the AAAA and CCCC sequences, favoring A-form helical conformations, while the UUUU sequence adopts an extended, heterogeneous structure. The mixed GACC sequence displays a predominantly A-form helix with flexible terminal residues. These results highlight the significant role of sequence in dictating RNA conformational spaces, which are driven by base stacking interactions and covalent geometry. We also emphasize the importance of enhanced sampling, particularly methods that can handle large numbers of collective variables, in evaluating RNA force fields, as traditional brute-force Molecular dynamics fails to capture the conformational diversity of flexible RNAs. Our study provides a reliable tool for RNA structure prediction and dynamic analysis, supporting future advancements in RNA-targeted research and therapeutic design.

The Journal of Chemical PhysicsVol. 162(20)
New York University Abu Dhabi (AE), New York University Shanghai (CN), Courant Institute of Mathematical Sciences (US), New York University (US)
New York University Abu Dhabi
Affordable and clean energy
Openalex Percentile: Top 8%
RNA and protein synthesis mechanisms
3.22
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.