Evidence map›Paper›PMID 31740721›Full record

ArticleScientific reports2019

Run length distribution of dimerized kinesin-3 molecular motors: comparison with dimeric kinesin-1.

Si-Kao Guo, Xiao-Xuan Shi, Peng-Ye Wang, Ping Xie

Abstract readComparative Study
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. A Model for Chemomechanical Coupling of Kinesin-3 Motor.Cellular and molecular bioengineering · 2024
    Article
  2. Article
  3. Article
  4. Modeling processive motion of kinesin-13 MCAK and kinesin-14 Cik1-Kar3 molecular motors.Protein science : a publication of the Protein Society · 2021
    Article
  5. Article
  6. Article
  7. 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.

Si-Kao GuoKey Laboratory of Soft Matter Physics, Institute of Physics, Chinese Academy of Science, Beijing, 100190, China.
Xiao-Xuan ShiKey Laboratory of Soft Matter Physics, Institute of Physics, Chinese Academy of Science, Beijing, 100190, China.
Peng-Ye WangKey Laboratory of Soft Matter Physics, Institute of Physics, Chinese Academy of Science, Beijing, 100190, China.
Ping XieKey Laboratory of Soft Matter Physics, Institute of Physics, Chinese Academy of Science, Beijing, 100190, China. pxie@aphy.iphy.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Kinesin-3 and kinesin-1 molecular motors are two families of the kinesin superfamily. It has been experimentally revealed that in monomeric state kinesin-3 is inactive in motility and cargo-mediated dimerization results in superprocessive motion, with an average run length being more than 10-fold longer than that of kinesin-1. In contrast to kinesin-1 showing normally single-exponential distribution of run lengths, dimerized kinesin-3 shows puzzlingly Gaussian distribution of run lengths. Here, based on our proposed model, we studied computationally the dynamics of kinesin-3 and compared with that of kinesin-1, explaining quantitatively the available experimental data and revealing the origin of superprocessivity and Gaussian run length distribution of kinesin-3. Moreover, predicted results are provided on ATP-concentration dependence of run length distribution and force dependence of mean run length and dissociation rate of kinesin-3.

Indexed as

Protein MultimerizationAdenosine DiphosphateAdenosine TriphosphateAlgorithmsAnimalsHumansKinesinsKineticsMicrotubulesMolecular Docking SimulationMolecular Dynamics SimulationMonte Carlo MethodProtein BindingAdenosine DiphosphateAdenosine TriphosphateKIF5B protein, humanKinesins

Identifiers

PMID31740721
PMCPMC6861319

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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.