mdRNAcat: A Molecular Dynamics RNA Catalog of REST2 Conformational Ensembles
Abstract
Learning molecular models of RNA requires simulation data that capture conformational variability and provide consistent physical training signals. Here, we introduce mdRNAcat, a curated dataset of all-atom molecular dynamics (MD) simulations of 48 RNA systems selected to promote sequence diversity. Each system is simulated using replica-exchange with solute scaling (REST2), with 32 Hamiltonian states and production lengths of 200-300 ns per state. The dataset provides atomic coordinates, instantaneous forces, and forces reevaluated under the unscaled reference Hamiltonian, together with structural annotations and replica-exchange metadata. Coordinates and forces are available at 1 ps intervals for the reference state and 100 ps intervals across all states in a standardized HDF5 format. We characterize conformational sampling, exchange behavior, base pairing, and sugar-pucker distributions to document the properties of the simulated ensembles. mdRNAcat provides a reusable resource for developing and evaluating data-driven RNA models, including coarse-grained force fields.
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BibTeX
@misc{dorn2026mdrnacat,
title = {{mdRNAcat: A Molecular Dynamics RNA Catalog of REST2 Conformational Ensembles}},
author = {Anton E. Dorn and Emile de Bruyn and Fabrice von der Lehr and Philipp Knechtges and Stefan Kesselheim and Alexander Schug},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.35204},
eprint = {2610.35204},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.35204},
}
RIS
TY - UNPB
TI - mdRNAcat: A Molecular Dynamics RNA Catalog of REST2 Conformational Ensembles
AU - Anton E. Dorn
AU - Emile de Bruyn
AU - Fabrice von der Lehr
AU - Philipp Knechtges
AU - Stefan Kesselheim
AU - Alexander Schug
PY - 2026
DA - 2026/10/27
PB - arXiv
DO - 10.48550/arxiv.2610.35204
UR - https://arxiv.org/abs/2610.35204
AB - Learning molecular models of RNA requires simulation data that capture conformational variability and provide consistent physical training signals. Here, we introduce mdRNAcat, a curated dataset of all-atom molecular dynamics (MD) simulations of 48 RNA systems selected to promote sequence diversity. Each system is simulated using replica-exchange with solute scaling (REST2), with 32 Hamiltonian states and production lengths of 200-300 ns per state. The dataset provides atomic coordinates, instantaneous forces, and forces reevaluated under the unscaled reference Hamiltonian, together with structural annotations and replica-exchange metadata. Coordinates and forces are available at 1 ps intervals for the reference state and 100 ps intervals across all states in a standardized HDF5 format. We characterize conformational sampling, exchange behavior, base pairing, and sugar-pucker distributions to document the properties of the simulated ensembles. mdRNAcat provides a reusable resource for developing and evaluating data-driven RNA models, including coarse-grained force fields.
ER -