ArticleThe journal of physical chemistry. B2011
Physics-based de novo prediction of RNA 3D structures.
Article in The journal of physical chemistry. B, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 103 papers.
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Who cites it
103 citing papers in PubMed.
- Crosstalk between RNA secondary and three-dimensional structure prediction: a comprehensive study.RNA biology · 2026Article
- Mechanistic Insights of miRNA Hybridization with ssDNA Self Assembled Monolayers on Gold Electrodes: An Electrochemical and Computational Study.Sensors and actuators. B, Chemical · 2026Article
- Hierarchical breakdown of RNA structure prediction in CASP16: from reliable local helices to speculative multimer assembly.Bioinformatics (Oxford, England) · 2026Article
- RNAbpFlow: base pair-augmented SE(3) flow matching for conditional RNA 3D structure generation.Nature methods · 2026Article
- In silico aptamer design: from sequence selection to structural optimization and computational modelling strategies.Journal of computer-aided molecular design · 2026Review
- Computational approaches for RNA structure prediction and design.Cell reports. Physical science · 2026Article
- TiRNA: a coarse-grained method with temperature and ion effects for RNA structure folding and prediction.Nucleic acids research · 2026Article
- Enhancing RNA 3D Structure Prediction in CASP16: Integrating Physics-Based Modeling With Machine Learning for Improved Predictions.Proteins · 2026Article
- Article
- Advances in Protein-RNA aptamer recognition and modeling: Current trends and future perspectives.Current opinion in structural biology · 2025Review
- RNAbpFlow: Base pair-augmented SE(3)-flow matching for conditional RNA 3D structure generation.bioRxiv : the preprint server for biology · 2025Article
- rsRNASP1: A distance- and dihedral-dependent statistical potential for RNA 3D structure evaluation.Biophysical journal · 2025Article
- Structural Prediction of Coronavirus s2m Kissing Complexes and Extended Duplexes.ACS physical chemistry Au · 2025Article
- Has AlphaFold3 achieved success for RNA?Acta crystallographica. Section D, Structural biology · 2025Article
- RNA-Puzzles Round V: blind predictions of 23 RNA structures.Nature methods · 2025Article
- Systematic benchmarking of deep-learning methods for tertiary RNA structure prediction.PLoS computational biology · 2024Article
- Machine learning in RNA structure prediction: Advances and challenges.Biophysical journal · 2024Review
- 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
- State-of-the-RNArt: benchmarking current methods for RNA 3D structure prediction.NAR genomics and bioinformatics · 2024Article
43 more citing papers are in PubMed but not listed here.
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Authors and funding
2 authors.
Funding
Abstract
Current experiments on structural determination cannot keep up the pace with the steadily emerging RNA sequences and new functions. This underscores the request for an accurate model for RNA three-dimensional (3D) structural prediction. Although considerable progress has been made in mechanistic studies, accurate prediction for RNA tertiary folding from sequence remains an unsolved problem. The first and most important requirement for the prediction of RNA structure from physical principles is an accurate free energy model. A recently developed three-vector virtual bond-based RNA folding model ("Vfold") has allowed us to compute the chain entropy and predict folding free energies and structures for RNA secondary structures and simple pseudoknots. Here we develop a free energy-based method to predict larger more complex RNA tertiary folds. The approach is based on a multiscaling strategy: from the nucleotide sequence, we predict the two-dimensional (2D) structures (defined by the base pairs and tertiary contacts); based on the 2D structure, we construct a 3D scaffold; with the 3D scaffold as the initial state, we combine AMBER energy minimization and PDB-based fragment search to predict the all-atom structure. A key advantage of the approach is the statistical mechanical calculation for the conformational entropy of RNA structures, including those with cross-linked loops. Benchmark tests show that the model leads to significant improvements in RNA 3D structure prediction.
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