Evidence map›Paper›PMID 33585149›Full record

ArticleBiophysics and physicobiology2020

GA-guided mD-VcMD: A genetic-algorithm-guided method for multi-dimensional virtual-system coupled molecular dynamics.

Junichi Higo, Ayumi Kusaka, Kota Kasahara, Narutoshi Kamiya, Itaya Hayato, Xie Qilin, Takuya Takahashi, Ikuo Fukuda, Kentaro Mori, Yutaka Hata and 1 more

Abstract read
In one paragraph

Article in Biophysics and physicobiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. 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

11 authors.

Junichi HigoGraduate School of Simulation Studies, University of Hyogo, Kobe, Hyogo 650-0047, Japan.
Ayumi KusakaInstitute for Protein Research, Osaka University, Suita, Osaka 565-0871, Japan.
Kota KasaharaCollege of Life Sciences, Ritsumeikan University, Kusatsu, Shiga 525-8577, Japan.
Narutoshi KamiyaGraduate School of Simulation Studies, University of Hyogo, Kobe, Hyogo 650-0047, Japan.
Itaya HayatoGraduate School of Life Sciences, Ritsumeikan University, Kusatsu, Shiga 525-8577, Japan.
Xie QilinCollege of Pharmaceutical Sciences, Ritsumeikan University, Kusatsu, Shiga 525-8577, Japan.
Takuya TakahashiCollege of Life Sciences, Ritsumeikan University, Kusatsu, Shiga 525-8577, Japan.
Ikuo FukudaGraduate School of Simulation Studies, University of Hyogo, Kobe, Hyogo 650-0047, Japan.
Kentaro MoriGraduate School of Simulation Studies, University of Hyogo, Kobe, Hyogo 650-0047, Japan.
Yutaka HataGraduate School of Simulation Studies, University of Hyogo, Kobe, Hyogo 650-0047, Japan.
Yoshifumi FukunishiCellular and Molecular Biotechnology Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Koto-ku, Tokyo, 135-0064, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We introduced a conformational sampling method in an earlier report: The multi-dimensional virtual-system coupled molecular dynamics (mD-VcMD) enhances conformational sampling of a biomolecular system by computer simulations. Herein, new sampling method, a subzone-based mD-VcMD, is presented as an extension of mD-VcMD. Then, the subzone-based method is extended further using a genetic algorithm (GA) named the GA-guided mD-VcMD. In these methods, iterative simulation runs are performed to increase the sampled region gradually. The new methods have the following benefits: (1) They are free from a production run: i.e., all snapshots from all iterations are useful for analyses. (2) They are free from fine tuning of a weight function (probability distribution function or potential of mean force). (3) A canonical ensemble (i.e., a thermally equilibrated ensemble) is generated from a simple procedure. A thermodynamic weight is assigned to each snapshot. (4) Selective sampling can be performed for particularly addressing a poorly sampled region without breaking the proportion of the canonical ensemble if the poorly sampled conformational region emerges in sampling. By applying the methods to a simple system that involves an energy barrier between potential-energy minima, we demonstrated that the new methods have considerably higher sampling efficiency than the original mD-VcMD does.

Indexed as

Canonical ensembleComputer simulationConformational samplingEnhanced samplingGeneralized ensemble

Identifiers

PMID33585149
PMCPMC7840461

What OpenQuestion holds

Textmetadata
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.