Evidence map›Paper›PMID 25185553›Full record

ArticleBiophysical journal2014

Stepping and crowding of molecular motors: statistical kinetics from an exclusion process perspective.

Luca Ciandrini, M Carmen Romano, Andrea Parmeggiani

Open access · bronzeAbstract read
In one paragraph

Article in Biophysical journal, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
3.7field-weighted citation impact, top 7% 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

3 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
  2. Article
  3. Sensitivity of mRNA Translation.Scientific reports · 2015
    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

3 authors at 2 institutions in 2 countries.

Luca CiandriniLaboratoire de Dynamique des Interactions Membranaires Normales et Pathologiques UMR 5235, Université Montpellier II and Centre National de la Recherche Scientifique, Montpellier, France; Laboratoire Charles Coulomb UMR 5221, Université Montpellier II and Centre National de la Recherche Scientifique, Montpellier, France. Electronic address: luca.ciandrini@univ-montp2.fr.
M Carmen RomanoInstitute for Complex Systems and Mathematical Biology, Scottish Universities Physics Alliance, University of Aberdeen, King's College, Aberdeen, United Kingdom; Institute of Medical Sciences, Foresterhill, University of Aberdeen, Aberdeen, United Kingdom.
Andrea ParmeggianiLaboratoire de Dynamique des Interactions Membranaires Normales et Pathologiques UMR 5235, Université Montpellier II and Centre National de la Recherche Scientifique, Montpellier, France; Laboratoire Charles Coulomb UMR 5221, Université Montpellier II and Centre National de la Recherche Scientifique, Montpellier, France.
Centre National de la Recherche Scientifique · FRUniversity of Aberdeen · GB

Funding

Biotechnology and Biological Sciences Research Council BB/F00513/X1Biotechnology and Biological Sciences Research Council BB/F00513X/1
6 · The paper itself

Abstract

Motor enzymes are remarkable molecular machines that use the energy derived from the hydrolysis of a nucleoside triphosphate to generate mechanical movement, achieved through different steps that constitute their kinetic cycle. These macromolecules, nowadays investigated with advanced experimental techniques to unveil their molecular mechanisms and the properties of their kinetic cycles, are implicated in many biological processes, ranging from biopolymerization (e.g., RNA polymerases and ribosomes) to intracellular transport (motor proteins such as kinesins or dyneins). Although the kinetics of individual motors is well studied on both theoretical and experimental grounds, the repercussions of their stepping cycle on the collective dynamics still remains unclear. Advances in this direction will improve our comprehension of transport process in the natural intracellular medium, where processive motor enzymes might operate in crowded conditions. In this work, we therefore extend contemporary statistical kinetic analysis to study collective transport phenomena of motors in terms of lattice gas models belonging to the exclusion process class. Via numerical simulations, we show how to interpret and use the randomness calculated from single particle trajectories in crowded conditions. Importantly, we also show that time fluctuations and non-Poissonian behavior are intrinsically related to spatial correlations and the emergence of large, but finite, clusters of comoving motors. The properties unveiled by our analysis have important biological implications on the collective transport characteristics of processive motor enzymes in crowded conditions.

Indexed as

Computer SimulationKineticsModels, MolecularModels, StatisticalMolecular Motor ProteinsNonlinear DynamicsMolecular Motor Proteins

Identifiers

PMID25185553
PMCPMC4156680
OpenAlexW2055596735

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.