Evidence map›Paper›PMID 34633813›Full record

ArticleJournal of chemical theory and computation2021

Similarities and Differences between Na

Egor S Kolesnikov, Ivan Yu Gushchin, Petr A Zhilyaev, Alexey V Onufriev

Open access · greenAbstract read
In one paragraph

Article in Journal of chemical theory and computation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.8field-weighted citation impact, top 14% of its field
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

11 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Fast Polarizable Water Model for Atomistic Simulations.Journal of chemical theory and computation · 2022
    Article
  9. Article
  10. Twisting DNA by salt.Nucleic acids research · 2022
    Article
  11. Article
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 at 3 institutions in 2 countries.

Egor S KolesnikovResearch Center for Molecular Mechanisms of Aging and Age-Related Diseases, Moscow Institute of Physics and Technology, Dolgoprudny 141700, Russia.
Ivan Yu GushchinResearch Center for Molecular Mechanisms of Aging and Age-Related Diseases, Moscow Institute of Physics and Technology, Dolgoprudny 141700, Russia.ORCID https://orcid.org/0000-0002-5348-6070
Petr A ZhilyaevCenter for Design, Manufacturing and Materials, Skolkovo Institute of Science and Technology, Bolshoy Boulevard 30, bld. 1, Moscow 121205, Russia.
Alexey V OnufrievDepartment of Computer Science, Virginia Tech, Blacksburg 24061-0131, United States.ORCID https://orcid.org/0000-0002-4930-6612
Moscow Institute of Physics and Technology · RUSkolkovo Institute of Science and Technology · RUVirginia Tech · US

Funding

Explicit ions in implicit solvent: fast and accurate.R21GM134404 · NIGMS · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI ONUFRIEV, ALEXEY VLAD · 2019 to 2020
$379k
NIGMS NIH HHS R21 GM134404
6 · The paper itself

Abstract

We have compared distributions of sodium and potassium ions around double-stranded DNA, simulated using fixed charge SPC/E, TIP3P, and OPC water models and the Joung/Cheatham (J/C) ion parameter set, as well as the Li/Merz HFE 6-12 (L/M HFE) ion parameters for OPC water. In all the simulations, the ion distributions are in qualitative agreement with Manning's condensation theory and the Debye-Hückel theory, where expected. In agreement with experiment, binding affinity of monovalent ions to DNA does not depend on ion type in every solvent model. However, behavior of deeply bound ions, including ions bound to specific sites, depends strongly on the solvent model. In particular, the number of potassium ions in the minor groove of AT-tracts differs at least 3-fold between the solvent models tested. The number of sodium ions associated with the DNA agrees quantitatively with the experiment for the OPC water model, followed closely by TIP3P+J/C; the largest deviation from the experiment, ∼10%, is seen for SPC/E+J/C. On the other hand, SPC/E+J/C model is most consistent (67%) with the experimental potassium binding sites, followed by OPC+J/C (60%), TIP3P+J/C (53%), and OPC+L/M HFE (27%). The use of NBFIX correction with TIP3P+J/C improves its consistency with the experiment. In summary, the choice of the solvent model matters little for simulating the diffuse atmosphere of sodium and potassium ions around DNA, but ion distributions become increasingly sensitive to the solvent model near the helical axis. We offer an explanation for these trends. There is no single gold standard solvent model, although OPC water with J/C ions or TIP3P with J/C + NBFIX may offer an imperfect compromise for practical simulations of ionic atmospheres around DNA.

Indexed as

Molecular Dynamics SimulationDNAIonsLithiumPotassiumSodiumSolventsWaterDNAIonsLithiumPotassiumSodiumSolventsWater

Identifiers

PMID34633813
PMCPMC10313235
OpenAlexW3206038369

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.