ReviewJournal of structural biology2019
Understanding the mechanistic basis of non-coding RNA through molecular dynamics simulations.
Review in Journal of structural biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 51 citations in OpenAlex.
- From gHBfix to NBfix: Reweighting-Driven Refinement of Hydrogen-Bond Interactions in RNA Force Fields.Journal of chemical theory and computation · 2026Article
- Toward Accurate RNA Folding Thermodynamics: Evaluation of Enhanced Sampling Methods for Force Field Benchmarking.Journal of chemical theory and computation · 2026Article
- Can We Ever Develop an Ideal RNA Force Field? Lessons Learned from Simulations of the UUCG RNA Tetraloop and Other Systems.Journal of chemical theory and computation · 2025Article
- The Unpaved Road of Non-Coding RNA Structure-Function Relationships: Current Knowledge, Available Methodologies, and Future Trends.Non-coding RNA · 2025Review
- How Binding Site Flexibility Promotes RNA Scanning by TbRGG2 RRM: A Molecular Dynamics Simulation Study.Journal of chemical information and modeling · 2025Article
- Comprehensive Assessment of Force-Field Performance in Molecular Dynamics Simulations of DNA/RNA Hybrid Duplexes.Journal of chemical theory and computation · 2024Article
- Binding Mechanism of Riboswitch to Natural Ligand Elucidated by McMD-Based Dynamic Docking Simulations.ACS omega · 2024Article
- Machines on Genes through the Computational Microscope.Journal of chemical theory and computation · 2023Review
- The Electronic Structure of Genome Editors from the First Principles.Electronic structure (Bristol, England) · 2023Article
- Spontaneous binding of single-stranded RNAs to RRM proteins visualized by unbiased atomistic simulations with a rescaled RNA force field.Nucleic acids research · 2022Article
- Emerging Methods and Applications to Decrypt Allostery in Proteins and Nucleic Acids.Journal of molecular biology · 2022Review
- Accelerating the Ensemble Convergence of RNA Hairpin Simulations with a Replica Exchange Structure Reservoir.Journal of chemical theory and computation · 2022Article
- 3D Modeling of Non-coding RNA Interactions.Advances in experimental medicine and biology · 2022Article
- Binding free energy decomposition and multiple unbinding paths of buried ligands in a PreQ1 riboswitch.PLoS computational biology · 2021Article
- Frontiers of metal-coordinating drug design.Expert opinion on drug discovery · 2021Review
- Atomic-scale insights into allosteric inhibition and evolutional rescue mechanism ofComputational and structural biotechnology journal · 2021Article
- Visualizing group II intron dynamics between the first and second steps of splicing.Nature communications · 2020Article
- Decrypting the Information Exchange Pathways across the Spliceosome Machinery.Journal of the American Chemical Society · 2020Article
- Recruiting Mechanism and Functional Role of a Third Metal Ion in the Enzymatic Activity of 5' Structure-Specific Nucleases.Journal of the American Chemical Society · 2020Article
- Disclosing the Impact of Carcinogenic SF3b Mutations on Pre-mRNA Recognition Via All-Atom Simulations.Biomolecules · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
Abstract
Noncoding RNA (ncRNA) has a key role in regulating gene expression, mediating fundamental processes and diseases via a variety of yet unknown mechanisms. Here, we review recent applications of conventional and enhanced Molecular Dynamics (MD) simulations methods to address the mechanistic function of large biomolecular systems that are tightly involved in the ncRNA function and that are of key importance in life sciences. This compendium focuses of three biomolecular systems, namely the CRISPR-Cas9 genome editing machinery, group II intron ribozyme and the ribonucleoprotein complex of the spliceosome, which edit and process ncRNA. We show how the application of a novel accelerated MD simulations method has been key in disclosing the conformational transitions underlying RNA binding in the CRISPR-Cas9 complex, suggesting a mechanism for RNA recruitment and clarifying the conformational changes required for attaining genome editing. As well, we discuss the use of mixed quantum-classical MD simulations in deciphering the catalytic mechanism of RNA splicing as operated by group II intron ribozyme, one of the largest ncRNA structures crystallized so far. Finally, we debate the future challenges and opportunities in the field, discussing the recent application of MD simulations for unraveling the functional biophysics of the spliceosome, a multi-mega Dalton complex of proteins and small nuclear RNAs that performs RNA splicing in humans. This showcase of applications highlights the current talent of MD simulations to dissect atomic-level details of complex biomolecular systems instrumental for the design of finely engineered genome editing machines. As well, this review aims at inspiring future investigations of several other ncRNA regulatory systems, such as micro and small interfering RNAs, which achieve their function and specificity using RNA-based recognition and targeting strategies.
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Registered trials
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.