RNA Dynamics and Interactions Revealed through Atomistic Simulations

2025/07/11 by Olivier Languin–Cattoën, Giovanni Bussi, Languin-Cattoën, Olivier +1 · 1 voice · 2 citations
Biochemistry, Genetics and Molecular Biology · #Biomolecules (q-bio.BM) #Chemical Physics (physics.chem-ph) #FOS: Biological sciences #FOS: Physical sciences

paper · doi:10.48550/arxiv.2507.08474

Abstract

RNA function is deeply intertwined with its conformational dynamics. In this review, we survey recent advances in the use of atomistic molecular dynamics simulations to characterize RNA dynamics in diverse contexts, including isolated molecules and complexes with ions, small molecules, or proteins. We highlight how enhanced sampling techniques and integrative approaches can improve both the precision and accuracy of the resulting structural ensembles. Finally, we examine the emerging role of artificial intelligence in accelerating progress in RNA modeling and simulation.

Citations

• Unique conformational dynamics and protein recognition of A-to-I hyper-edited dsRNA
• The Kink-Turn Motif: A Powerful Test for Revealing Weaknesses in RNA Force Fields
• Grand canonical Monte Carlo and deep learning assisted enhanced sampling to characterize the distribution of Mg2+ and influence of the Drude polarizable force field on the stability of folded states of the twister ribozyme
• Characterizing RNA oligomers using Stochastic Titration Constant-pH Metadynamics simulations
• Ensemble refinement of mismodeled cryo-EM RNA structures using all-atom simulations
• Deep learning path-like collective variable for enhanced sampling molecular dynamics
• Inferring phase transitions and critical exponents from limited observations with Thermodynamic Maps
• Impact of 2′‐hydroxyl sampling on the conformational properties of RNA: Update of the CHARMM all‐atom additive force field for RNA

Cited by

• Enhanced sampling and cryo-EM data resolve magnesium binding to RNA
• Unraveling the Mechanism of Drug Binding to SARS‐CoV‐2 RNA Pseudoknot With Thermodynamics‐Driven Machine Learning

Discussions

• 📢 New #preprint alert! Our review "RNA Dynamics and Interactions Revealed through Atomistic Simulations" is now available on arxiv.org/abs/2507.08474 ! Written by @bussigio.bsky.social and @ollyfutur [bsky, 7 points, 1 comments]

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