Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Computing Curvature Sensitivity of Biomolecules in Membranes by Simulated Buckling
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Faculty of Science, Department of Materials and Environmental Chemistry (MMK).
Stockholm University, Faculty of Science, Department of Materials and Environmental Chemistry (MMK).
Stockholm University, Faculty of Science, Department of Materials and Environmental Chemistry (MMK).ORCID iD: 0000-0002-5496-4695
Number of Authors: 42018 (English)In: Journal of Chemical Theory and Computation, ISSN 1549-9618, E-ISSN 1549-9626, Vol. 14, no 3, p. 1643-1655Article in journal (Refereed) Published
Abstract [en]

Membrane curvature sensing, where the binding free energies of membrane-associated molecules depend on the local membrane curvature, is a key factor to modulate and maintain the shape and organization of cell membranes. However, the microscopic mechanisms are not well understood, partly due to absence of efficient simulation methods. Here, we describe a method to compute the curvature dependence of the binding free energy of a membrane associated probe molecule that interacts with a buckled membrane, which has been created by lateral compression of a flat bilayer patch. This buckling approach samples a wide range of curvatures in a single simulation, and anisotropic effects can be extracted from the orientation statistics. We develop an efficient and robust algorithm to extract the motion of the probe along the buckled membrane surface, and evaluate its numerical properties by extensive sampling of three coarse-grained model systems: local lipid density in a curved environment for single-component bilayers, curvature preferences of individual lipids in two-component membranes, and curvature sensing by a homotrimeric transmembrane protein. The method can be used to complement experimental data from curvature partition assays and provides additional insight into mesoscopic theories and molecular mechanisms for curvature sensing.

Place, publisher, year, edition, pages
2018. Vol. 14, no 3, p. 1643-1655
National Category
Biophysics
Research subject
Biophysics
Identifiers
URN: urn:nbn:se:su:diva-154791DOI: 10.1021/acs.jctc.7b00878ISI: 000427661400043PubMedID: 29350922OAI: oai:DiVA.org:su-154791DiVA, id: diva2:1198244
Available from: 2018-04-17 Created: 2018-04-17 Last updated: 2018-06-21Bibliographically approved
In thesis
1.
The record could not be found. The reason may be that the record is no longer available or you may have typed in a wrong id in the address field.

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMed

Search in DiVA

By author/editor
Elías-Wolff, FedericoLindén, MartinLyubartsev, Alexander P.Brandt, Erik G.
By organisation
Department of Biochemistry and BiophysicsDepartment of Materials and Environmental Chemistry (MMK)
In the same journal
Journal of Chemical Theory and Computation
Biophysics

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 12 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf