Evidence map›Paper›PMID 19754142›Full record

ArticleAccounts of chemical research2010

Molecular dynamics and quantum mechanics of RNA: conformational and chemical change we can believe in.

Mark A Ditzler, Michal Otyepka, Jirì Sponer, Nils G Walter

Abstract read
In one paragraph

Article in Accounts of chemical research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

64 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. RNA 3D Modeling with FARFAR2, Online.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
  6. Article
  7. Article
  8. Organic & biomolecular chemistry · 2022
    Article
  9. Article
  10. Heliyon · 2020
    Article
  11. Article
  12. Article
  13. Article
  14. Using Rosetta for RNA homology modeling.Methods in enzymology · 2019
    Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Physics-based all-atom modeling of RNA energetics and structure.Wiley interdisciplinary reviews. RNA · 2017
    Review
  20. Article

4 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Mark A DitzlerBiophysics, University of Michigan, 930 North University Avenue, Ann Arbor, Michigan 48109-1055, USA.
Michal Otyepka
Jirì Sponer
Nils G Walter

Funding

U-turn of the Hepatitis Delta Virus RibozymeR01GM062357 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI WALTER, NILS G · 2001 to 2019
$5.8M
NIGMS NIH HHS GM62357NIGMS NIH HHS R01 GM062357
6 · The paper itself

Abstract

Structure and dynamics are both critical to RNA's vital functions in biology. Numerous techniques can elucidate the structural dynamics of RNA, but computational approaches based on experimental data arguably hold the promise of providing the most detail. In this Account, we highlight areas wherein molecular dynamics (MD) and quantum mechanical (QM) techniques are applied to RNA, particularly in relation to complementary experimental studies. We have expanded on atomic-resolution crystal structures of RNAs in functionally relevant states by applying explicit solvent MD simulations to explore their dynamics and conformational changes on the submicrosecond time scale. MD relies on simplified atomistic, pairwise additive interaction potentials (force fields). Because of limited sampling, due to the finite accessible simulation time scale and the approximated force field, high-quality starting structures are required. Despite their imperfection, we find that currently available force fields empower MD to provide meaningful and predictive information on RNA dynamics around a crystallographically defined energy minimum. The performance of force fields can be estimated by precise QM calculations on small model systems. Such calculations agree reasonably well with the Cornell et al. AMBER force field, particularly for stacking and hydrogen-bonding interactions. A final verification of any force field is accomplished by simulations of complex nucleic acid structures. The performance of the Cornell et al. AMBER force field generally corresponds well with and augments experimental data, but one notable exception could be the capping loops of double-helical stems. In addition, the performance of pairwise additive force fields is obviously unsatisfactory for inclusion of divalent cations, because their interactions lead to major polarization and charge-transfer effects neglected by the force field. Neglect of polarization also limits, albeit to a lesser extent, the description accuracy of other contributions, such as interactions with monovalent ions, conformational flexibility of the anionic sugar-phosphate backbone, hydrogen bonding, and solute polarization by solvent. Still, despite limitations, MD simulations are a valid tool for analyzing the structural dynamics of existing experimental structures. Careful analysis of MD simulations can identify problematic aspects of an experimental RNA structure, unveil structural characteristics masked by experimental constraints, reveal functionally significant stochastic fluctuations, evaluate the structural role of base ionization, and predict structurally and potentially functionally important details of the solvent behavior, including the presence of tightly bound water molecules. Moreover, combining classical MD simulations with QM calculations in hybrid QM/MM approaches helps in the assessment of the plausibility of chemical mechanisms of catalytic RNAs (ribozymes). In contrast, the reliable prediction of structure from sequence information is beyond the applicability of MD tools. The ultimate utility of computational studies in understanding RNA function thus requires that the results are neither blindly accepted nor flatly rejected, but rather considered in the context of all available experimental data, with great care given to assessing limitations through the available starting structures, force field approximations, and sampling limitations. The examples given in this Account showcase how the judicious use of basic MD simulations has already served as a powerful tool to help evaluate the role of structural dynamics in biological function of RNA.

Indexed as

Computational BiologyModels, MolecularMolecular ConformationMolecular Dynamics SimulationNucleic Acid ConformationQuantum TheoryRNARNA

Identifiers

PMID19754142
PMCPMC2808146

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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.