Non-equilibrium effects of molecular motors on polymers.


Journal

Soft matter
ISSN: 1744-6848
Titre abrégé: Soft Matter
Pays: England
ID NLM: 101295070

Informations de publication

Date de publication:
24 Jul 2019
Historique:
pubmed: 12 7 2019
medline: 12 7 2019
entrez: 12 7 2019
Statut: ppublish

Résumé

We present a generic coarse-grained model to describe molecular motors acting on polymer substrates, mimicking, for example, RNA polymerase on DNA or kinesin on microtubules. The polymer is modeled as a connected chain of beads; motors are represented as freely diffusing beads which, upon encountering the substrate, bind to it through a short-ranged attractive potential. When bound, motors and polymer beads experience an equal and opposite active force, directed tangential to the polymer; this leads to motion of the motors along the polymer contour. The inclusion of explicit motors differentiates our model from other recent active polymer models. We study, by means of Langevin dynamics simulations, the effect of the motor activity on both the conformational and dynamical properties of the substrate. We find that activity leads, in addition to the expected enhancement of polymer diffusion, to an effective reduction of its persistence length. We discover that this effective "softening" is a consequence of the emergence of double-folded branches, or hairpins, and that it can be tuned by changing the number of motors or the force they generate. Finally, we investigate the effect of the motors on the probability of knot formation. Counter-intuitively our simulations reveal that, even though at equilibrium a more flexible substrate would show an increased knotting probability, motor activity leads to a marked decrease in the occurrence of knotted conformations with respect to equilibrium.

Identifiants

pubmed: 31292585
doi: 10.1039/c9sm00273a
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

5995-6005

Auteurs

M Foglino (M)

SUPA, School of Physics and Astronomy, University of Edinburgh, Edinburgh EH9 3FD, UK.

Classifications MeSH