Evidence map›Paper›PMID 35381009›Full record

ArticlePLoS computational biology2022

Implementation of residue-level coarse-grained models in GENESIS for large-scale molecular dynamics simulations.

Cheng Tan, Jaewoon Jung, Chigusa Kobayashi, Diego Ugarte La Torre, Shoji Takada, Yuji Sugita

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
6.2field-weighted citation impact, top 2% 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

40 citing papers in PubMed, 78 citations in OpenAlex.

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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

6 authors at 3 institutions in 1 country.

Cheng TanComputational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo, Japan.ORCID 0000-0002-8957-4267
Jaewoon JungComputational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo, Japan.ORCID 0000-0002-2285-4432
Chigusa KobayashiComputational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo, Japan.ORCID 0000-0002-5603-4619
Diego Ugarte La TorreComputational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo, Japan.ORCID 0000-0002-8391-8065
Shoji TakadaDepartment of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan.ORCID 0000-0001-5385-7217
Yuji SugitaComputational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo, Japan.ORCID 0000-0001-9738-9216
RIKEN Center for Computational Science · JPRIKEN · JPKyoto University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Residue-level coarse-grained (CG) models have become one of the most popular tools in biomolecular simulations in the trade-off between modeling accuracy and computational efficiency. To investigate large-scale biological phenomena in molecular dynamics (MD) simulations with CG models, unified treatments of proteins and nucleic acids, as well as efficient parallel computations, are indispensable. In the GENESIS MD software, we implement several residue-level CG models, covering structure-based and context-based potentials for both well-folded biomolecules and intrinsically disordered regions. An amino acid residue in protein is represented as a single CG particle centered at the Cα atom position, while a nucleotide in RNA or DNA is modeled with three beads. Then, a single CG particle represents around ten heavy atoms in both proteins and nucleic acids. The input data in CG MD simulations are treated as GROMACS-style input files generated from a newly developed toolbox, GENESIS-CG-tool. To optimize the performance in CG MD simulations, we utilize multiple neighbor lists, each of which is attached to a different nonbonded interaction potential in the cell-linked list method. We found that random number generations for Gaussian distributions in the Langevin thermostat are one of the bottlenecks in CG MD simulations. Therefore, we parallelize the computations with message-passing-interface (MPI) to improve the performance on PC clusters or supercomputers. We simulate Herpes simplex virus (HSV) type 2 B-capsid and chromatin models containing more than 1,000 nucleosomes in GENESIS as examples of large-scale biomolecular simulations with residue-level CG models. This framework extends accessible spatial and temporal scales by multi-scale simulations to study biologically relevant phenomena, such as genome-scale chromatin folding or phase-separated membrane-less condensations.

Indexed as

Molecular Dynamics SimulationSoftwareChromatinDNAChromatinDNA

Identifiers

PMID35381009
PMCPMC9012402
OpenAlexW4226017322

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.