ArticleJournal of chemical theory and computation2016
Monte Carlo Tightly Bound Ion Model: Predicting Ion-Binding Properties of RNA with Ion Correlations and Fluctuations.
Article in Journal of chemical theory and computation, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 44 citations in OpenAlex.
- A cooperative effect of ligands, MgThe Journal of biological chemistry · 2026Article
- Driving forces of RNA condensation revealed through coarse-grained modeling with explicit MgProceedings of the National Academy of Sciences of the United States of America · 2025Article
- Magnesium ions mediate ligand binding and conformational transition of the SAM/SAH riboswitch.Communications biology · 2023Article
- Magnesium ions mediate ligand binding and conformational transition of the SAM/SAH riboswitch.bioRxiv : the preprint server for biology · 2023Article
- Landscape Zooming toward the Prediction of RNA Cotranscriptional Folding.Journal of chemical theory and computation · 2022Article
- Graph deep learning locates magnesium ions in RNA.QRB discovery · 2022Article
- Binding free energy decomposition and multiple unbinding paths of buried ligands in a PreQ1 riboswitch.PLoS computational biology · 2021Article
- Thermostability, Tunability, and Tenacity of RNA as Rubbery Anionic Polymeric Materials in Nanotechnology and Nanomedicine-Specific Cancer Targeting with Undetectable Toxicity.Chemical reviews · 2021Review
- RLDOCK: A New Method for Predicting RNA-Ligand Interactions.Journal of chemical theory and computation · 2020Article
- Modeling Loop Composition and Ion Concentration Effects in RNA Hairpin Folding Stability.Biophysical journal · 2020Article
- New opportunities for designing effective small interfering RNAs.Scientific reports · 2019Article
- Predicting Monovalent Ion Correlation Effects in Nucleic Acids.ACS omega · 2019Article
- Site-Specific Binding of Non-Site-Specific Ions.Biophysical journal · 2019Article
- Predicting RNA-Metal Ion Binding with Ion Dehydration Effects.Biophysical journal · 2019Article
- RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview.Chemical reviews · 2018Review
- Hexahydrated MgBiophysical journal · 2018Article
- Nuclear Magnetic Resonance Study of RNA Structures at the 3'-End of the Hepatitis C Virus Genome.Biochemistry · 2017Article
- Predicting Ion Effects in an RNA Conformational Equilibrium.The journal of physical chemistry. B · 2017Article
- MCTBI: a web server for predicting metal ion effects in RNA structures.RNA (New York, N.Y.) · 2017Article
- Theory and Modeling of RNA Structure and Interactions with Metal Ions and Small Molecules.Annual review of biophysics · 2017Review
Corrections and comments
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Authors and funding
2 authors at 1 institution in 2 countries.
Funding
Abstract
Experiments have suggested that ion correlation and fluctuation effects can be potentially important for multivalent ions in RNA folding. However, most existing computational methods for the ion electrostatics in RNA folding tend to ignore these effects. The previously reported tightly bound ion (TBI) model can treat ion correlation and fluctuation but its applicability to biologically important RNAs is severely limited by the low computational efficiency. Here, on the basis of Monte Carlo sampling for the many-body ion distribution, we develop a new computational model, the Monte Carlo tightly bound ion (MCTBI) model, for ion-binding properties around an RNA. Because of an enhanced sampling algorithm for ion distribution, the model leads to a significant improvement in computational efficiency. For example, for a 160-nt RNA, the model causes a more than 10-fold increase in the computational efficiency, and the improvement in computational efficiency is more pronounced for larger systems. Furthermore, unlike the earlier model that describes ion distribution using the number of bound ions around each nucleotide, the current MCTBI model is based on the three-dimensional coordinates of the ions. The higher efficiency of the model allows us to treat the ion effects for medium to large RNA molecules, RNA-ligand complexes, and RNA-protein complexes. This new model together with proper RNA conformational sampling and the energetics model may serve as a starting point for further development for the ion effects in RNA folding and conformational changes and for large nucleic acid systems.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.