Evidence map›Paper›PMID 29605930›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2018

A Multiscale Computational Model for Simulating the Kinetics of Protein Complex Assembly.

Jiawen Chen, Yinghao Wu

Abstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.0field-weighted citation impact, top 15% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Multiscale simulation unravel the kinetic mechanisms of inflammasome assembly.Biochimica et biophysica acta. Molecular cell research · 2020
    Article
  3. Article
  4. 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

2 authors at 1 institution in 1 country.

Jiawen ChenDepartment of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY, USA.
Yinghao WuDepartment of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY, USA. yinghao.wu@einstein.yu.edu.
Albert Einstein College of Medicine · US

Funding

A multiscale model for binding kinetics of membrane receptors on cell surfacesR01GM120238 · NIGMS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI WU, YINGHAO · 2016 to 2020
$1.6M
NIGMS NIH HHS R01 GM120238
6 · The paper itself

Abstract

Proteins fulfill versatile biological functions by interacting with each other and forming high-order complexes. Although the order in which protein subunits assemble is important for the biological function of their final complex, this kinetic information has received comparatively little attention in recent years. Here we describe a multiscale framework that can be used to simulate the kinetics of protein complex assembly. There are two levels of models in the framework. The structural details of a protein complex are reflected by the residue-based model, while a lower-resolution model uses a rigid-body (RB) representation to simulate the process of complex assembly. These two levels of models are integrated together, so that we are able to provide the kinetic information about complex assembly with both structural details and computational efficiency.

Indexed as

Models, StatisticalMolecular Dynamics SimulationProtein Interaction Domains and MotifsAlgorithmsComputational BiologyHumansKineticsMonte Carlo MethodMultiprotein ComplexesProtein BindingProteinsMultiprotein ComplexesProteinsCoarse-grained simulationDiffusion-reaction algorithmKinetic Monte CarloMultiscale modelingProtein association rateProtein complex assembly

Identifiers

PMID29605930
PMCPMC6003773
OpenAlexW2795120695

What OpenQuestion holds

Textmetadata
LicenceTDM
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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.