Issue 72, 2018

The penetration of a charged peptide across a membrane under an external electric field: a coarse-grained molecular dynamics simulation

Abstract

The processes of single polyarginine (R8) peptide penetration through planar and vesicle membranes under an external electric field are simulated via a coarse-grained molecular dynamics (CGMD) simulation. The results show that the external electric field can greatly enhance the penetration possibility of the R8 peptide through membranes. For different membranes (planar membrane and curved vesicle membrane), the amplitudes of electric fields needed for penetration are different. The penetration time of the R8 peptide across membranes decreases with the increasing amplitude of the external electric field applied. Under a constant electric field, the length of penetration time for different membranes is also different. For a better understanding of the mechanism of the penetration, we analyzed the Potential Mean Force (PMF) of the R8-membrane systems and found that the PMFs of the planar membrane and the curved vesicle membrane have a large difference. This may be one of the main factors that induces the different penetration processes of the R8 peptide across membranes when they respond to the same external electric field. All these findings shed light on the role of external electric field on the penetration of R8 peptide through membranes and also give some insights into the effects of membrane curvature on the transportation processes of the peptide carriers.

Graphical abstract: The penetration of a charged peptide across a membrane under an external electric field: a coarse-grained molecular dynamics simulation

Article information

Article type
Paper
Submitted
14 Sep 2018
Accepted
28 Nov 2018
First published
11 Dec 2018
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2018,8, 41517-41525

The penetration of a charged peptide across a membrane under an external electric field: a coarse-grained molecular dynamics simulation

B. Wang, J. Zhang, Y. Zhang, Z. Mao, N. Lu and Q. H. Liu, RSC Adv., 2018, 8, 41517 DOI: 10.1039/C8RA07654E

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