Evidence map›Paper›PMID 31984192›Full record

ArticleBiophysics and physicobiology2019

Combination of coarse-grained molecular dynamics simulations and small-angle X-ray scattering experiments.

Toru Ekimoto, Yuichi Kokabu, Tomotaka Oroguchi, Mitsunori Ikeguchi

Open access · goldAbstract read
In one paragraph

Article in Biophysics and physicobiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 54% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Review
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 2 institutions in 1 country.

Toru EkimotoGraduate School of Medical Life Science, Yokohama City University, Yokohama, Kanagawa 230-0045, Japan.
Yuichi KokabuBioscience Department, Mitsui Knowledge Industry Co., Ltd., Minato-ku, Tokyo 105-6215, Japan.
Tomotaka OroguchiGraduate School of Medical Life Science, Yokohama City University, Yokohama, Kanagawa 230-0045, Japan.
Mitsunori IkeguchiGraduate School of Medical Life Science, Yokohama City University, Yokohama, Kanagawa 230-0045, Japan.
Yokohama City University · JPKeio University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The combination of molecular dynamics (MD) simulations and small-angle X-ray scattering (SAXS), called the MD-SAXS method, is efficient for investigating protein dynamics. To overcome the time-scale limitation of all-atom MD simulations, coarse-grained (CG) representations are often utilized for biomolecular simulations. In this study, we propose a method to combine CG MD simulations with SAXS, termed the CG-MD-SAXS method. In the CG-MD-SAXS method, the scattering factors of CG particles for proteins and nucleic acids are evaluated using high-resolution structural data in the Protein Data Bank, and the excluded volume and the hydration shell are modeled using two adjustable parameters to incorporate solvent effects. To avoid overfitting, only the two parameters are adjusted for an entire structure ensemble. To verify the developed method, theoretical SAXS profiles for various proteins, DNA/RNA, and a protein-RNA complex are compared with both experimental profiles and theoretical profiles obtained by the all-atom representation. In the present study, we applied the CG-MD-SAXS method to the Swi5-Sfr1 complex and three types of nucleosomes to obtain reliable ensemble models consistent with the experimental SAXS data.

Indexed as

MD simulationnucleosomeprotein solution structureSAXSstructural ensemble

Identifiers

PMID31984192
PMCPMC6976007
OpenAlexW2991372532

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.