Efficient RNA Folding Simulation via a Structure-Based Single-Site-Per-Nucleotide Model

Abstract

Computational modeling of large RNA structures and their dynamics is essential for uncovering the molecular mechanisms underlying various genomic processes and RNA-regulated cellular functions. Residue-resolution modeling is an effective approach for simulating large biomolecular structures while preserving essential sequence and struc-tural features presented in atomic structures. Here, we implemented a structure-based single-site-per-nucleotide (SSPN) RNA model using the GPU-accelerated OpenMM 1 software and evaluated its computational efficiency and accuracy by simulating RNA hairpins unfolding under force. Our simulations compare favorably with an earlier, more detailed RNA model and quantitatively reproduce experimentally measured ther-modynamic properties of RNA under mechanical stretching. This SSPN model enables scalable and accurate simulations of large RNA ensembles, such as long non-coding RNAs and RNA liquid-liquid phase separation.