ArticleRNA (New York, N.Y.)2008
Ab initio RNA folding by discrete molecular dynamics: from structure prediction to folding mechanisms.
Article in RNA (New York, N.Y.), 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 162 papers.
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Who cites it
162 citing papers in PubMed.
- Building RNA coarse-grained force fields: Design principles and training strategies.Biophysical journal · 2026Review
- PlanarFold: a coarse-grained molecular dynamics model of RNA in two-dimensional space.Nature communications · 2026Article
- TiRNA: a coarse-grained method with temperature and ion effects for RNA structure folding and prediction.Nucleic acids research · 2026Article
- Advances in Protein-RNA aptamer recognition and modeling: Current trends and future perspectives.Current opinion in structural biology · 2025Review
- rsRNASP1: A distance- and dihedral-dependent statistical potential for RNA 3D structure evaluation.Biophysical journal · 2025Article
- Structural Impact of 3-methylcytosine Modification on the Anticodon Stem-loop of a Neuronally-enriched Arginine tRNA.Journal of molecular biology · 2025Article
- Reconfigurable Nucleic Acid Nanoparticles with Therapeutic RNAi Responses to Intracellular Disease Markers.Advanced functional materials · 2025Article
- Computational exploration of the self-aggregation mechanisms of phenol-soluble modulins β1 and β2 in Staphylococcus aureus biofilms.Colloids and surfaces. B, Biointerfaces · 2025Article
- RNA-Puzzles Round V: blind predictions of 23 RNA structures.Nature methods · 2025Article
- Review
- mRNA vaccine sequence and structure design and optimization: Advances and challenges.The Journal of biological chemistry · 2025Review
- Systematic benchmarking of deep-learning methods for tertiary RNA structure prediction.PLoS computational biology · 2024Article
- RNA ensembles from in vitro to in vivo: Toward predictive models of RNA cellular function.Current opinion in structural biology · 2024Review
- Unveiling the double-edged sword: SOD1 trimers possess tissue-selective toxicity and bind septin-7 in motor neuron-like cells.Structure (London, England : 1993) · 2024Article
- Predicting 3D RNA structure from the nucleotide sequence using Euclidean neural networks.Biophysical journal · 2024Article
- Comparative analysis of RNA 3D structure prediction methods: towards enhanced modeling of RNA-ligand interactions.Nucleic acids research · 2024Article
- Tying the knot: Unraveling the intricacies of the coronavirus frameshift pseudoknot.PLoS computational biology · 2024Article
- Differentiable rotamer sampling with molecular force fields.Briefings in bioinformatics · 2023Article
- Functional filter for whole-genome sequencing data identifies HHT and stress-associated non-coding SMAD4 polyadenylation site variants >5 kb from coding DNA.American journal of human genetics · 2023Article
- RNA 3D Structure Prediction: Progress and Perspective.Molecules (Basel, Switzerland) · 2023Review
102 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
Funding
Abstract
RNA molecules with novel functions have revived interest in the accurate prediction of RNA three-dimensional (3D) structure and folding dynamics. However, existing methods are inefficient in automated 3D structure prediction. Here, we report a robust computational approach for rapid folding of RNA molecules. We develop a simplified RNA model for discrete molecular dynamics (DMD) simulations, incorporating base-pairing and base-stacking interactions. We demonstrate correct folding of 150 structurally diverse RNA sequences. The majority of DMD-predicted 3D structures have <4 A deviations from experimental structures. The secondary structures corresponding to the predicted 3D structures consist of 94% native base-pair interactions. Folding thermodynamics and kinetics of tRNA(Phe), pseudoknots, and mRNA fragments in DMD simulations are in agreement with previous experimental findings. Folding of RNA molecules features transient, non-native conformations, suggesting non-hierarchical RNA folding. Our method allows rapid conformational sampling of RNA folding, with computational time increasing linearly with RNA length. We envision this approach as a promising tool for RNA structural and functional analyses.
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